Sentiment Based Movie Rating System

Data mining, Networking, Web | Desktop Application
Sentiment Based Movie Rating System We usually come across movie rating websites where users are allowed to rate ad comment on movies online. These ratings are provided as input to the website rating system. The admin then checks reviews, critic’s ratings and displays an online rating for every movie. Here we propose an online system that automatically allows users to post reviews and stores them to rate movies based on user sentiments. The system now analyzes this data to check for user sentiments associated with each comment. Our system consists of a sentiment library designed for English as well as hindi sentiment analysis. The system breaks user comments to check for sentimental keywords and predicts user sentiment associated with it. Once the keywords are found it associates the comment with…
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Heart Disease Prediction Project

Data mining, Multimedia, Web | Desktop Application
Heart Disease Prediction Project It might have happened so many times that you or someone yours need doctors help immediately, but they are not available due to some reason. The Heart Disease Prediction application is an end user support and online consultation project. Here, we propose a web application that allows users to get instant guidance on their heart disease through an intelligent system online. The application is fed with various details and the heart disease associated with those details. The application allows user to share their heart related issues. It then processes user specific details to check for various illness that could be associated with it. Here we use some intelligent data mining techniques to guess the most accurate illness that could be associated with patient’s details. Based on…
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Detecting Fraud Apps Using Sentiment Analysis

Data mining, Networking, Web | Desktop Application
Detecting Fraud Apps Using Sentiment Analysis Most of us use android and IOS Mobiles these days and also uses the play store or app store capability normally. Both the stores provide great number of application but unluckily few of those applications are fraud. Such applications dose damage to phone and also may be data thefts. Hence, such applications must be marked, so that they will be identifiable for store users. So we are proposing a web application which will process the information, comments and the review of the application. So it will be easier to decide which application is fraud or not. Multiple application can be processed at a time with the web application. Also User cannot always get correct or true reviews about the product on internet. So rating/comments…
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Encryption & Decryption Using Deffie Hellman Algorithm

Multimedia, Security and Encryption, Web | Desktop Application
Encryption & Decryption Using Deffie Hellman Algorithm The spectacular growth of the Internet has spawned an increased awareness of and interest in security issues. Although security has been considered in the design of the basic Internet protocols, many applications have been and are being designed with minimal attention paid to issues of confidentiality, authentication, and privacy. As our daily activities become more and more reliant upon data networks, the importance of an understanding of such security issues will only increase. Many cryptographic algorithms (e.g., DES, AES) require the establishment of shared keying material in advance. Manual distribution of keying material is inefficient and complex. This is where the Diffie-Hellman Key Agreement algorithm is useful. The project is developed using Visual Studio with C# .Net as programming language. There is only…
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Balancing Performance, Accuracy, and Precision for Secure Cloud Transactions

Cloud Computing, Web | Desktop Application
Balancing Performance, Accuracy, and Precision for Secure Cloud Transactions In distributed transactional database systems deployed over cloud servers, entities cooperate to form proofs of authorizations that are justified by collections of certified credentials. These proofs and credentials may be evaluated and collected over extended time periods under the risk of having the underlying authorization policies or the user credentials being in inconsistent states. It therefore becomes possible for policy-based authorization systems to make unsafe decisions that might threaten sensitive resources. In this paper, we highlight the criticality of the problem. We then define the notion of trusted transactions when dealing with proofs of authorization. Accordingly, we propose several increasingly stringent levels of policy consistency constraints, and present different enforcement approaches to guarantee the trustworthiness of transactions executing on cloud servers. We propose a Two-Phase Validation Commit protocol…
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A Secure and Dynamic Multi-keyword Ranked Search Scheme over Encrypted Cloud Data

Cloud Computing, Security and Encryption
A Secure and Dynamic Multi-keyword Ranked Search Scheme over Encrypted Cloud Data The project defines and solve the problem of multi-keyword ranked search over encrypted cloud data (MRSE) while preserving strict system wise privacy in the cloud computing paradigm. Data owners are motivated to outsource their complex data management systems from local sites to the commercial public cloud for great flexibility and economic savings. But for protecting data privacy, sensitive data have to be encrypted before outsourcing, which obsoletes traditional data utilization based on plaintext keyword search. Thus, enabling an encrypted cloud data search service is of paramount importance. Considering the large number of data users and documents in the cloud, it is necessary to allow multiple keywords in the search request and return documents in the order of their…
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Design of a Secured E-voting System

Android Mobile development
Design of a Secured E-voting System E-voting systems are becoming popular with the widespread use of computers and embedded systems. Security is the vital issue should be considered in such systems. This paper proposes a new e-voting system that fulfills the security requirements of e-voting. It is based on homomorphic property and blind signature scheme. The proposed system is implemented on an embedded system which serves as a voting machine. The system employes RFID to store all conditions that comply with the rule of the government to check voter eligibility.
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Shopping Application System With Near Field Communication (NFC) Based on Android

Android Mobile development, Web | Desktop Application
Shopping Application System With Near Field Communication (NFC) Based on Android The rapid development of mobile communications systems today, along with the changing times and technology, both in terms of hardware, operating system used and the use of Internet bandwidth, making some mobile applications also contribute to exploit these developments. Mobile Commerce Applications for an example, became the most popular applications for mobile users who do not want to trouble yourself with having to carry cash everywhere. An important technology behind mobile payments is called Near Field Communication (NFC). As an indication that NFC represents the potential and tremendous business, leading companies such as Nokia, Microsoft and NXP Semiconductors, actively engaged in the NFC Forum. Shopping application process integrated with NFC technologybased on Android. Shopping application system designed, for the…
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Developing an Android based Learning Application for Mobile Devices

Android Mobile development
Developing an Android based Learning Application for Mobile Devices his paper is about the development of MLEA, a platform that assists, through Android cellphones and tablets, the mobility of users of learning virtual environments. MLEA is an application that implements computational techniques such as web services, design patterns, ontologies, and mobile computational techniques in order to allow the communication between mobile devices and the content management system – Moodle. It´s based on a service oriented, client server architecture that combines the REST protocol and JSON format for data interchange. The client will be provided with features for alerts, file downloads, chats and forums, grade books, quizzes, and calendar, among others.
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Location Based Reminder Using GPS For Mobile

Android Mobile development
Location Based Reminder Using GPS For Mobile Although location-based reminder applications have been widely prototyped, there are few results regarding their impact on people: how are they used, do they change people’s behavior and what features influence usefulness the most. Cell phones provide a compelling platform for the delivery of location-based reminders within a user's everyday natural context. We present requirements for location-based reminders resulting from a qualitative study performed at small area in the city, and elaborate how these results are influencing ongoing design of a more comprehensive location-based reminder system. In this paper we propose an architecture of location based services which uses GPS. Within the architecture, we discuss the challenges for context management, service trigger mechanism and preference-based services.
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Learn to Personalized Image Search from the Photo Sharing Websites

Multimedia, Web | Desktop Application
Learn to Personalized Image Search from the Photo Sharing Websites Increasingly developed social sharing websites, like Flickr and Youtube, allow users to create, share, annotate and comment Medias. The large-scale usergenerated meta-data not only facilitate users in sharing and organizing multimedia content, but provide useful information to improve media retrieval and management. Personalized search serves as one of such examples where the web search experience is improved by generating the returned list according to the modified user search intents. In this paper, we exploit the social annotations and propose a novel framework simultaneously considering the user and query relevance to learn to personalized image search. The basic premise is to embed the user preference and query-related search intent into user-specific topic spaces. Since the users’ original annotation is too sparse…
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Trust modeling in social tagging of multimedia content.

Multimedia
Trust modeling in social tagging of multimedia content. Tagging in online social networks is very popular these days, as it facilitates search and retrieval of multimedia content. However, noisy and spam annotations often make it difficult to perform an efficient search. Users may make mistakes in tagging and irrelevant tags and content may be maliciously added for advertisement or self-promotion. This article surveys recent advances in techniques for combatting such noise and spam in social tagging. We classify the state-of-the-art approaches into a few categories and study representative examples in each. We also qualitatively compare and contrast them and outline open issues for future research.
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Persuasive Cued Click-Points: Design, implementation, and evaluation of a knowledge-based authentica

Multimedia, Security and Encryption
Persuasive Cued Click-Points: Design, implementation, and evaluation of a knowledge-based authentication Increasingly developed social sharing websites, like Flickr and Youtube, allow users to create, share, annotate and comment Medias. The large-scale usergenerated meta-data not only facilitate users in sharing and organizing multimedia content, but provide useful information to improve media retrieval and management. Personalized search serves as one of such examples where the web search experience is improved by generating the returned list according to the modified user search intents. In this paper, we exploit the social annotations and propose a novel framework simultaneously considering the user and query relevance to learn to personalized image search. The basic premise is to embed the user preference and query-related search intent into user-specific topic spaces. Since the users’ original annotation is too…
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BECAN: A Bandwidth-Efficient Cooperative Authentication Scheme for Filtering Injected False Data in

Parallel And Distributed System
BECAN: A Bandwidth-Efficient Cooperative Authentication Scheme for Filtering Injected False Data in Injecting false data attack is a well known serious threat to wireless sensor network, for which an adversary reports bogus information to sink causing error decision at upper level and energy waste in en-route nodes. In this paper, we propose a novel bandwidth-efficient cooperative authentication (BECAN) scheme for filtering injected false data. Based on the random graph characteristics of sensor node deployment and the cooperative bit-compressed authentication technique, the proposed BECAN scheme can save energy by early detecting and filtering the majority of injected false data with minor extra overheads at the en-route nodes. In addition, only a very small fraction of injected false data needs to be checked by the sink, which thus largely reduces the burden…
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Privacy-Preserving Updates to Anonymous and Confidential Databases

Parallel And Distributed System, Web | Desktop Application
Privacy-Preserving Updates to Anonymous and Confidential Databases Suppose Alice owns a k-anonymous database and needs to determine whether her database, when inserted with a tuple owned by Bob, is still k-anonymous. Also, suppose that access to the database is strictly controlled, because for example data are used for certain experiments that need to be maintained confidential. Clearly, allowing Alice to directly read the contents of the tuple breaks the privacy of Bob (e.g., a patient’s medical record); on the other hand, the confidentiality of the database managed by Alice is violated once Bob has access to the contents of the database. Thus, the problem is to check whether the database inserted with the tuple is still k-anonymous, without letting Alice and Bob know the contents of the tuple and the…
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The Geometric Efficient Matching Algorithm for Firewalls

Parallel And Distributed System, Web | Desktop Application
The Geometric Efficient Matching Algorithm for Firewalls The firewall is one of the central technologies allowing high-level access control to organization networks. Packet matching in firewalls involves matching on many fields from the TCP and IP packet header. At least five fields (protocol number, source and destination IP addresses, and ports) are involved in the decision which rule applies to a given packet. With available bandwidth increasing rapidly, very efficient matching algorithms need to be deployed in modern firewalls to ensure that the firewall does not become a bottleneck Since firewalls need to filter all the traffic crossing the network perimeter, they should be able to sustain a very high throughput, or risk becoming a bottleneck. Thus, algorithms from computational geometry can be applied. In this paper we consider a…
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In Cloud, Can Scientific Communities Benefit from the Economies of Scale?

Parallel And Distributed System, Web | Desktop Application
In Cloud, Can Scientific Communities Benefit from the Economies of Scale? The basic idea behind Cloud computing is that resource providers offer elastic resources to end users. In this paper, we intend to answer one key question to the success of Cloud computing: in Cloud, can small or medium-scale scientific computing communities benefit from the economies of scale? Our research contributions are three fold: first, we propose an enhanced scientific public cloud model (ESP) that encourages small or medium scale research organizations rent elastic resources from a public cloud provider; second, on a basis of the ESP model, we design and implement the Dawning Cloud system that can consolidate heterogeneous scientific workloads on a Cloud site; third, we propose an innovative emulation methodology and perform a comprehensive evaluation. We found…
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A NOVEL ANTI PHISHING FRAMEWORK BASED ON VISUAL CRYPTOGRAPHY

Parallel And Distributed System, Security and Encryption, Web | Desktop Application
A NOVEL ANTI PHISHING FRAMEWORK BASED ON VISUAL CRYPTOGRAPHY Phishing is an attempt by an individual or a group to thieve personal confidential information such as passwords, credit card information etc from unsuspecting victims for identity theft, financial gain and other fraudulent activities. In this paper we have proposed a new approach named as "A Novel Anti phishing framework based on visual cryptography" to solve the problem of phishing. Here an image based authentication using Visual Cryptography (vc) is used. The use of visual cryptography is explored to preserve the privacy of image captcha by decomposing the original image captcha into two shares that are stored in separate database servers such that the original image captcha can be revealed only when both are simultaneously available; the individual sheet images do…
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Balancing the Tradeoffs between Query Delay and Data Availability in MANETs.

Parallel And Distributed System, Web | Desktop Application
Balancing the Tradeoffs between Query Delay and Data Availability in MANETs. In mobile ad hoc networks (MANETs), nodes move freely and link/node failures are common, which leads to frequent network partitions. When a network partition occurs, mobile nodes in one partition are not able to access data hosted by nodes in other partitions, and hence significantly degrade the performance of data access. To deal with this problem, we apply data replication techniques. Existing data replication solutions in either wired or wireless networks aim at either reducing the query delay or improving the data availability, but not both. As both metrics are important for mobile nodes, we propose schemes to balance the tradeoffs between data availability and query delay under different system settings and requirements. Extensive simulation results show that the…
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Resource-Aware Application State Monitoring.

Parallel And Distributed System
Resource-Aware Application State Monitoring. The increasing popularity of large-scale distributed applications in datacenters has led to the growing demand of distributed application state monitoring. These application state monitoring tasks often involve collecting values of various status attributes from a large number of nodes. One challenge in such large-scale application state monitoring is to organize nodes into a monitoring overlay that achieves monitoring scalability and cost-effectiveness at the same time. In this paper, we present REMO, a REsource-aware application state MOnitoring system, to address the challenge of monitoring overlay construction. REMO distinguishes itself from existing works in several key aspects. First, it jointly considers inter-task costsharing opportunities and node-level resource constraints. Furthermore, it explicitly models the per-message processing overhead which can be substantial but is often ignored by previous works. Second,…
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SPOC: A Secure and Privacy-preserving Opportunistic Computing Framework for Mobile-Healthcare Emerge

Parallel And Distributed System, Web | Desktop Application
SPOC: A Secure and Privacy-preserving Opportunistic Computing Framework for Mobile-Healthcare Emerge With the pervasiveness of smart phones and the advance of wireless body sensor networks (BSNs), mobile Healthcare (m-Healthcare), which extends the operation of Healthcare provider into a pervasive environment for better health monitoring, has attracted considerable interest recently. However, the flourish of m-Healthcare still faces many challenges including information security and privacy preservation. In this paper, we propose a secure and privacy-preserving opportunistic computing framework, called SPOC, for m-Healthcare emergency. With SPOC, smart phone resources including computing power and energy can be opportunistically gathered to process the computing intensive personal health information (PHI) during m-Healthcare emergency with minimal privacy disclosure. In specific, to leverage the PHI privacy disclosure and the high reliability of PHI process and transmission in m-Healthcare…
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Cooperative Provable Data Possession for Integrity Verification in Multi-Cloud Storage.

Parallel And Distributed System, Web | Desktop Application
Cooperative Provable Data Possession for Integrity Verification in Multi-Cloud Storage. Provable data possession (PDP) is a technique for ensuring the integrity of data in storage outsourcing. In this paper, we address the construction of an efficient PDP scheme for distributed cloud storage to support the scalability of service and data migration, in which we consider the existence of multiple cloud service providers to cooperatively store and maintain the clients’ data. We present a cooperative PDP (CPDP) scheme based on homomorphic verifiable response and hash index hierarchy. We prove the security of our scheme based on multi-prover zero-knowledge proof system, which can satisfy completeness, knowledge soundness, and zero-knowledge properties. In addition, we articulate performance optimization mechanisms for our scheme, and in particular present an efficient method for selecting optimal parameter values…
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Location Based Services using Android Mobile Operating System

Android Mobile development, Web | Desktop Application
Location Based Services using Android Mobile Operating System The motivation for every location based information system is: “To assist with the exact information, at right place in real time with personalized setup and location sensitiveness”. In this era we are dealing with palmtops and iPhones, which are going to replace the bulky desktops even for computational purposes. We have vast number of applications and usage where a person sitting in a roadside café needs to get relevant data and information. Such needs can only be catered with the help of LBS. These applications include security related jobs, general survey regarding traffic patterns, decision based on vehicular information for validity of registration and license numbers etc. A very appealing application includes surveillance where instant information is needed to decide if the…
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OCRAndroid: A Framework to Digitize Text Using Mobile Phones

Android Mobile development
OCRAndroid: A Framework to Digitize Text Using Mobile Phones As demand grows for mobile phone applications, research in optical character recognition, a technology well developed for scanned documents, is shifting focus to the recognition of text embedded in digital photographs. In this paper, we present OCRdroid, a generic framework for developing OCR-based applications on mobile phones. OCRdroid combines a light-weight image preprocessing suite installed inside the mobile phone and an OCR engine connected to a backend server. We demonstrate the power and functionality of this framework by implementing two applications called PocketPal and PocketReader based on OCRdroid on HTC Android G1 mobile phone. Initial evaluations of these pilot experiments demonstrate the potential of using OCRdroid framework for realworld OCR-based mobile applications.
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Mobile Phone Based Drunk Driving Detection

Android Mobile development
Mobile Phone Based Drunk Driving Detection Drunk driving, or officially Driving Under the Influence (DUI) of alcohol, is a major cause of traffic accidents throughout the world. In this paper, we propose a highly efficient system aimed at early detection and alert of dangerous vehicle maneuvers typically related to drunk driving. The entire solution requires only a mobile phone placed in vehicle and with accelerometer and orientation sensor. A program installed on the mobile phone computes accelerations based on sensor readings, and compares them with typical drunk driving patterns extracted from real driving tests. Once any evidence of drunk driving is present, the mobile phone will automatically alert the driver or call the police for help well before accident actually happens. We implement the detection system on Android G1 phone…
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Android based elimination of potholes

Android Mobile development, Web | Desktop Application
Android based elimination of potholes Its a web based project where user or normal residential people can complain about their nearby potholes. They can take an image of it and upload it to submit to BMC department. Every user will have their own credentials to login and to view the potholes. BMC will have their own admin login details to look after the posting and tackle or reply to each complaints so that they can sort those problem as soon as possible.
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A Personalized Mobile Search Engine

Android Mobile development
A Personalized Mobile Search Engine We propose a personalized mobile search engine, PMSE, that captures the users’ preferences in the form of concepts by mining their clickthrough data. Due to the importance of location information in mobile search, PMSE classifies these concepts into content concepts and location concepts. In addition, users’ locations (positioned by GPS) are used to supplement the location concepts in PMSE. The user preferences are organized in an ontology-based, multi-facet user profile, which are used to adapt a personalized ranking function for rank adaptation of future search results. To characterize the diversity of the concepts associated with a query and their relevances to the users need, four entropies are introduced to balance the weights between the content and location facets. Based on the client-server model, we also…
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Designing the Next Generation of Mobile Tourism Application based on Situation Awareness

Android Mobile development
Designing the Next Generation of Mobile Tourism Application based on Situation Awareness Mobile tourism applications are changing the way travelers plan and experience tourism in the years to come. A large and growing body of literature has investigated the development of context awareness mobile applications for tourism industry. Various aspects of context awareness are studied and applied in tour guide companions and recommendation systems. However, these context awareness mobile applications do not improve traveler’s situation awareness especially in pre-visiting and during visiting phases. In other words, when using mobile applications, travelers may not perceive the situation correctly, fail to comprehend the situation or they are unable to anticipate the future development. This paper proposes a theoretical approach for designing mobile tourism applications using situation awareness. Three scenarios of traveler visiting…
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Semisupervised Biased Maximum Margin Analysis for Interactive Image Retrieval.

Image Processing
Semisupervised Biased Maximum Margin Analysis for Interactive Image Retrieval. With many potential practical applications, content- based image retrieval (CBIR) has attracted substantial attention during the past few years. A variety of relevance feedback (RF) schemes have been developed as a powerful tool to bridge the semantic gap between low-level visual features and high-level semantic concepts, and thus to improve the performance of CBIR systems. Among various RF approaches, support-vector-machine (SVM)-based RF is one of the most popular techniques in CBIR. Despite the success, directly using SVM as an RF scheme has two main drawbacks. First, it treats the positive and negative feedbacks equally, which is not appropriate since the two groups of training feedbacks have distinct properties. Second, most of the SVM-based RF techniques do not take into account the…
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Automatic image equalization and contrast enhancement using Gaussian mixture

Image Processing, Web | Desktop Application
Automatic image equalization and contrast enhancement using Gaussian mixture Abstract In this paper, we propose an adaptive image equalization algorithm which automatically enhances the contrast in an input image. The algorithm uses Gaussian mixture model (GMM) to model the image grey-level distribution, and the intersection points of the Gaussian components in the model are used to partition the dynamic range of the image into input grey-level intervals. The contrast equalized image is generated by transforming the pixels’ grey levels in each input interval to the appropriate output grey-level interval according to the dominant Gaussian component and cumulative distribution function (CDF) of the input interval. To take account of human perception the Gaussian components with small variances are weighted with smaller values than the Gaussian components with larger variances, and the…
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Scalable Face Image Retrieval using Attribute-Enhanced Sparse Codewords

Image Processing, Web | Desktop Application
Scalable Face Image Retrieval using Attribute-Enhanced Sparse Codewords Photos with people (e.g., family, friends, celebrities, etc.) are the major interest of users. Thus, with the exponentially growing photos, large-scale content-based face image retrieval is an enabling technology for many emerging applications. In this work, we aim to utilize automatically detected human attributes that contain semantic cues of the face photos to improve content- based face retrieval by constructing semantic codewords for effi-cient large-scale face retrieval. By leveraging human attributes in a scalable and systematic framework, we propose two orthogonal methods named attribute-enhanced sparse coding and attribute- embedded inverted indexing to improve the face retrieval in the offline and online stages. We investigate the effectiveness of different attributes and vital factors essential for face retrieval. Experimenting on two public datasets, the…
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CloudProtect: Managing Data Privacy in Cloud Applications

Cloud Computing, Web | Desktop Application
CloudProtect: Managing Data Privacy in Cloud Applications This paper describes the CloudProtect middleware that empowers users to encrypt sensitive data stored within various cloud applications. However, most web applications require data in plaintext for implementing the various functionalities and in general, do not support encrypted data management. Therefore, CloudProtect strives to carry out the data transformations (encryption/decryption) in a manner that is transparent to the application, i.e., preserves all functionalities of the application, including those that require data to be in plaintext. Additionally, CloudProtect allows users flexibility in trading off performance for security in order to let them optimally balance their privacy needs and usage-experience.
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An effective image steganalysis method based on neighborhood information of pixels

Image Processing, Web | Desktop Application
An effective image steganalysis method based on neighborhood information of pixels This project focuses on image steganalysis. We use higher order image statistics based on neighborhood information of pixels (NIP) to detect the stego images from original ones. We use subtracting gray values of adjacent pixels to capture neighborhood information, and also make use of ―rotation invariant‖ property to reduce the dimensionality for the whole feature sets. We tested two kinds of NIP feature, the experimental results illustrates that our proposed feature sets are with good performance and even outperform the state-of-art in certain aspect.
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A Secured Cost-effective Multi-Cloud Storage in Cloud Computing.

Cloud Computing, Web | Desktop Application
The end of this decade is marked by a paradigm shift of the industrial information technology towards a pay-per-use service business model known as cloud computing. Cloud data Storage redefines the security issues targeted on customer’s outsourced data (data that is not stored/retrieved from the costumers own servers). In this work we observed that, from a customer’s point of view, relying upon a solo SP for his outsourced data is not very promising. In addition, providing better privacy as well as ensuring data availability can be achieved by dividing the user’s data block into data pieces and distributing them among the available SPs in such a way that no less than a threshold number of SPs can take part in successful retrieval of the whole data block. In this paper,…
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Ensuring Data Storage Security in Cloud Computing

Cloud Computing, Web | Desktop Application
Ensuring Data Storage Security in Cloud Computing Cloud computing has been envisioned as the next-generation architecture of IT enterprise. In contrast to traditional solutions, where the IT services are under proper physical, logical and personnel controls, cloud computing moves the application software and databases to the large data centers, where the management of the data and services may not be fully trustworthy. This unique attribute, however, poses many new security challenges which have not been well understood. In this article, we focus on cloud data storage security, which has always been an important aspect of quality of service. To ensure the correctness of users' data in the cloud, we propose an effective and flexible distributed scheme with two salient features, opposing to its predecessors. By utilizing the homomorphic token with…
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Automatic Plant Leaf Classification for a Mobile Field Guide

Image Processing
Automatic Plant Leaf Classification for a Mobile Field Guide In this paper we describe the development of an Android application that gives users the ability to identify plant species based on photographs of the plant’s leaves taken with a mobile phone. At the heart of this application is an algorithm that acquires morphological features of the leaves, computes welldocumented metrics such as the angle code histogram (ACH), then classifies the species based on a novel combination of the computed metrics. The algorithm is first trained against several samples of known plant species and then used to classify unknown query species. Aided by features designed into the application such as touchscreen image rotation and contour preview, the algorithm is very successful in properly classifying species contained in the training library.
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Fuzzy Keyword Search over Encrypted Data in Cloud Computing

Cloud Computing
Fuzzy Keyword Search over Encrypted Data in Cloud Computing As Cloud Computing becomes prevalent, more and more sensitive information are being centralized into the cloud. Although traditional searchable encryption schemes allow a user to securely search over encrypted data through keywords and selectively retrieve files of interest, these techniques support only exact keyword search. In this paper, for the first time we formalize and solve the problem of effective fuzzy keyword search over encrypted cloud data while maintaining keyword privacy. Fuzzy keyword search greatly enhances system usability by returning the matching files when users’ searching inputs exactly match the predefined keywords or the closest possible matching files based on keyword similarity semantics, when exact match fails. In our solution, we exploit edit distance to quantify keywords similarity and develop two…
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Secure And Authenticated Reversible Data Hiding In Encrypted Images

Image Processing, Web | Desktop Application
Secure And Authenticated Reversible Data Hiding In Encrypted Images Reversible data hiding a novel technique which is used to embed additional information in the encrypted images, applies in military and medical images, which can be recoverable with original media and the hided data without loss. A number of reversible data hiding techniques were proposed in the recent years, but on analysis, all lacks in providing the security and authentication. This project proposes a novel reversible data hiding technique which work is separable, the receiver can extract the original image or extra embedded data or both according to the keys hold by the receiver. On the other hand the receiver can verify the data hided by the data hider, such that the work proposes both security and authentication. This project proposes…
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Developing Secure Social Healthcare System over the Cloud

Cloud Computing, Web | Desktop Application
Developing Secure Social Healthcare System over the Cloud Healthcare application is a social media application which is developed over the cloud. Now a day we hear two cutting edge technologies most social media and cloud computing. Developing and maintaining a healthcare system with self infrastructure well cost more. Many small hospitals save hard copies of patient’s records. This healthcare application will provide web service which is developed over the cloud so it well reduces the cost and they need not be worried about infrastructure. Cloud providers well provide up to date software so, software well be up to date. Since data is present in the cloud most of them worry about security. By using role based access control healthcare system is secured.
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Access Control Mechanisms for Outsourced Data in Cloud

Cloud Computing, Web | Desktop Application
Access Control Mechanisms for Outsourced Data in Cloud Traditional access control models often assume that the en- tity enforcing access control policies is also the owner of data and re- sources. This assumption no longer holds when data is outsourced to a third-party storage provider, such as the cloud. Existing access control solutions mainly focus on preserving con dentiality of stored data from unauthorized access and the storage provider. However, in this setting, access control policies as well as users' access patterns also become pri- vacy sensitive information that should be protected from the cloud. We propose a two-level access control scheme that combines coarse-grained access control enforced at the cloud, which allows to get acceptable com- munication overhead and at the same time limits the information that the cloud learns…
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An extended visual cryptography scheme without pixel expansion for halftone images

Image Processing, Web | Desktop Application
An extended visual cryptography scheme without pixel expansion for halftone images Visual cryptography is a secret sharing scheme which use images distributed as shares such that, when the shares are superimposed, a hidden secret image is revealed. In extended visual cryptography, the share images are constructed to contain meaningful cover images, thereby providing opportunities for integrating visual cryptography and biometric security techniques. In this paper, we propose a method for processing halftone images that improves the quality of the share images and the recovered secret image in an extended visual cryptography scheme for which the size of the share images and the recovered image is the same as for the original halftone secret image. The resulting scheme maintains the perfect security of the original extended visual cryptography approach.
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Cloud Data Protection for the Masses

Cloud Computing, Web | Desktop Application
Cloud Data Protection for the Masses Offering strong data protection to cloud users while enabling rich applications is a challenging task. We explore a new cloud platform architecture called Data Protection as a Service, which dramatically reduces the per-application development effort required to offer data protection, while still allowing rapid development and maintenance.
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Dynamic Bandwidth Allocation in Cloud Computing

Cloud Computing, Web | Desktop Application
Dynamic Bandwidth Allocation in Cloud Computing Cloud Computing is a use of computing resources that is delivered as a service over a network. Sharing the data in the cloud depends on the network performance of the data centers. Bandwidth allocation plays a major role in sharing the resources towards the data center networks. Server performance is the major problem in cloud computing. When multiple users send a request for the same server at a time, the performance of the server is considerably decreased. So we describe a novel method of reallocating the bandwidth dynamically from passive users to active users using bandwidth mutual sharing and fair sharing technique.
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A Secret-Sharing-Based Method for Authentication of Grayscale Document Images via the Use of the PNG

Image Processing, Web | Desktop Application
A Secret-Sharing-Based Method for Authentication of Grayscale Document Images via the Use of the PNG Abstract—A new blind authentication method based on the secret sharing technique with a data repair capability for grayscale document images via the use of the PNG image is proposed. An authentication signal is generated for each block of a grayscale document image, which, together with the binarized block content, is transformed into several shares using the Shamir secret sharing scheme. The involved parameters are carefully chosen so that as many shares as possible are generated and embedded into an alpha channel plane. The alpha channel plane is then combined with the original grayscale image to form a PNG image. During the embedding process, the computed share values are mapped into a range of alpha channel…
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DEFENSES AGAINST LARGE SCALE ONLINE PASSWORD GUESSING ATTACKS BY USING PERSUASIVE CLICK POINTS

Cloud Computing, Web | Desktop Application
DEFENSES AGAINST LARGE SCALE ONLINE PASSWORD GUESSING ATTACKS BY USING PERSUASIVE CLICK POINTS Abstract Usable security has unique usability challenges because the need for security often means that standard human-computer-interaction approaches cannot be directly applied. An important usability goal for authentication systems is to support users in selecting better passwords. Users often create memorable passwords that are easy for attackers to guess, but strong system-assigned passwords are difficult for users to remember. So researchers of modern days have gone for alternative methods wherein graphical pictures are used as passwords. Graphical passwords essentially use images or representation of images as passwords. Human brain is good in remembering picture than textual character. There are various graphical password schemes or graphical password software in the market. However, very little research has been done…
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Robust Face-Name Graph Matching for Movie Character Identification

Image Processing, Web | Desktop Application
Robust Face-Name Graph Matching for Movie Character Identification Automatic face identification of characters in movies has drawn significant research interests and led to many interesting applications. It is a challenging problem due to the huge variation in the appearance of each character. Although existing methods demonstrate promising results in clean environment, the performances are limited in complex movie scenes due to the noises generated during the face tracking and face clustering process. In this paper we present two schemes of global face-name matching based framework for robust character identification. The contributions of this work include: 1) A noise insensitive character relationship representation is incorporated. 2) We introduce an edit operation based graph matching algorithm. 3) Complex character changes are handled by simultaneously graph partition and graph matching. 4) Beyond existing…
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A DYMANIC METHOD TO SECURE CONFIDENTIAL DATA USING SIGNCRYPTION WITH STEGANOGRAPHY

Image Processing, Web | Desktop Application
A DYMANIC METHOD TO SECURE CONFIDENTIAL DATA USING SIGNCRYPTION WITH STEGANOGRAPHY Since years due to the increase of technology, the means of communication and transferring information from one point to the other has been drastically changed. Because of this rapid development of technology, few people misusing the technology to unveil the confidential data. To provide high end security to the data to prevent form the attackers we are proposing a dynamic method in this paper. Two things are important to provide security to the data confidentiality and encryption. In this paper we are using signcryption technique to provide high security to the data, by encrypting the data with digital signature, because of this the attacker cannot do any kind of modification to the data in case the data is decrypted…
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Mitigating of fire based disaster using IP

Image Processing, Web | Desktop Application
Mitigating of fire based disaster using IP Present work is an in depth study to detect flames in video by processing the data captured by an ordinary camera. Previous vision based methods were based on color difference, motion detection of flame pixel and flame edge detection. This paper focuses on optimizing the flame detection by identifying gray cycle pixels nearby the flame, which is generated because of smoke and of spreading of fire pixel and the area spread of flame. These techniques can be used to reduce false alarms along with fire detection methods . The novel system simulate the existing fire detection techniques with above given new techniques of fire detection and give optimized way to detect the fire in terms of less false alarms by giving the accurate…
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A Novel Data Embedding Method Using Adaptive Pixel Pair Matching

Image Processing, Web | Desktop Application
A Novel Data Embedding Method Using Adaptive Pixel Pair Matching This paper proposes a new data-hiding method based on pixel pair matching (PPM). The basic idea of PPM is to use the values of pixel pair as a reference coordinate, and search a coordinate in the neighborhood set of this pixel pair according to a given message digit. The pixel pair is then replaced by the searched coordinate to conceal the digit. Exploiting modification direction (EMD) and diamond encoding (DE) are two data-hiding methods proposed recently based on PPM. The maximum capacity of EMD is 1.161 bpp and DE extends the payload of EMD by embedding digits in a larger notational system. The proposed method offers lower distortion than DE by providing more compact neighborhood sets and allowing embedded digits…
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A Keyless Approach to Image Encryption

Image Processing, Security and Encryption, Web | Desktop Application
A Keyless Approach to Image Encryption Maintaining the secrecy and confidentiality of images is a vibrant area of research, with two different approaches being followed, the first being encrypting the images through encryption algorithms using keys, the other approach involves dividing the image into random shares to maintain the images secrecy. Unfortunately heavy computation cost and key management limit the employment of the first approach and the poor quality of the recovered image from the random shares limit the applications of the second approach. In this paper we propose a novel approach without the use of encryption keys. The approach employs Sieving, Division and Shuffling to generate random shares such that with minimal computation, the original secret image can be recovered from the random shares without any loss of image…
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Efficient Privacy-Preserving Range Queries over Encrypted Data in Cloud Computing

Cloud Computing, Web | Desktop Application
Efficient Privacy-Preserving Range Queries over Encrypted Data in Cloud Computing With the growing popularity of data and service outsourcing, where the data resides on remote servers in encrypted form, there remain open questions about what kind of query operations can be performed on the encrypted data. In this paper, we focus on one such important query operation, namely range query. One of the basic security primitive that can be used to evaluate range queries is secure comparison of encrypted integers. However, the existing secure comparison protocols strongly rely on the encrypted bit-wise representations rather than on pure encrypted integers. Therefore, in this paper, we first propose an efficient method for converting an encrypted integer z into encryptions of the individual bits of z. We then utilize the proposed security primitive…
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N-Square Approach For Lossless Image Compression And Decompression

Image Processing, Web | Desktop Application
N-Square Approach For Lossless Image Compression And Decompression There are several lossy and lossless coding techniques developed all through the last two decades. Although very high compression can be achieved with lossy compression techniques, they are deficient in obtaining the original image. While lossless compression technique recovers the image exactly. In applications related to medical imaging lossless techniques are required, as the loss of information is deplorable. The objective of image compression is to symbolize an image with a handful number of bits as possible while preserving the quality required for the given application. In this paper we are introducing a new lossless encoding and decoding technique which even better reduces the entropy there by reducing the average number of bits with the utility of Non Binary Huffman coding through…
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An Efficient Real Time Moving Object Detection Method for Video Surveillance System

Image Processing, Web | Desktop Application
An Efficient Real Time Moving Object Detection Method for Video Surveillance System Moving object detection has been widely used in diverse discipline such as intelligent transportation systems, airport security systems, video monitoring systems, and so on. In this paper, we propose an efficient moving object detection method using enhanced edge localization mechanism and gradient directional masking for video surveillance system. In our proposed method, gradient map images are initially generated from the input and background images using a gradient operator. The gradient difference map is then calculated from gradient map images. The moving object is then detected by using appropriate directional masking and thresholding. Simulation results indicate that the proposed method consistently performs well under different illumination conditions including indoor, outdoor, sunny, and foggy cases. Moreover, it outperforms well known…
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Image Authentication and Restoration using BlockWise Fragile Watermarking based on k-Medoids Clustering Approach

Image Processing, Web | Desktop Application
Image Authentication and Restoration using BlockWise Fragile Watermarking based on k-Medoids Clustering Approach This paper proposes a block-wise fragile watermarking scheme based on k-medoids clustering approach. Proposed scheme is effective enough to reconstruct the tampered extensive content of an image. According to the suggested algorithm, first of all image is divided into the blocks and forty eight bits are calculated for each block, which consist of forty five Recovery bits and three Authentication bits namely Union bit, Affiliation bit and Spectrum bit. Authentication bits for a particular block are calculated by extracting five MSBs from each pixel of that block and apply them, on some predefined hash functions. Forty five Recovery bits are calculated using the means of derived clusters and its corresponding mapping bits. These Forty eight bits for…
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A robust skew detection method based on maximum gradient difference and R-signature

Image Processing, Web | Desktop Application
A robust skew detection method based on maximum gradient difference and R-signature In this paper we study the detection of skewed text lines in scanned document images. The aim of our work is to develop a new automatic approach able to estimate precisely the skew angle of text in document images. Our new method is based on Maximum Gradient Difference (MGD) and R-signature. It detects zones that have high variations of gray values in different directions using the MGD transform. We consider these zones as being text regions. R-signature which is a shape descriptor based on Radon transform is then applied in order to approximate the skew angle. The accuracy of the proposed algorithm is evaluated on an open dataset by comparing error rates.
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Image-based object detection under varying illumination in environments with specular surfaces

Image Processing, Web | Desktop Application
Image-based object detection under varying illumination in environments with specular surfaces Image-based environment representations capture the appearance of the surroundings of a mobile robot and are useful for the detection of novelty. However, image-based novelty detection can be impaired by illumination effects. In this paper we present an approach for the image-based detection of novel objects in a scene under varying lighting conditions and in the presence of objects with specular surfaces. The computation of an illumination-invariant image-based environment representation allows for the extraction of the shading of the environment from camera images. Using statistical models infered from the luminance and the saturation component of the shading images, secularities and shadows are detected and suppressed in the process of novelty detection. Experimental results show that the proposed method outperforms two…
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A New Block Compressive Sensing to Control the Number of Measurements

Image Processing, Web | Desktop Application
A New Block Compressive Sensing to Control the Number of Measurements Compressive Sensing (CS) aims to recover a sparse signal from a small number of projections onto random vectors. Be- cause of its great practical possibility, both academia and in- dustries have made efforts to develop the CS’s reconstruction performance, but most of existing works remain at the theo- retical study. In this paper, we propose a new Block Compres- sive Sensing (nBCS), which has several benefits compared to the general CS methods. In particular, the nBCS can be dynamically adaptive to varying channel capacity because it conveys the good inheritance of the wavelet transform.
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Secure Authentication using Image Processing and Visual Cryptography for Banking Applications

Image Processing, Web | Desktop Application
Secure Authentication using Image Processing and Visual Cryptography for Banking Applications Core banking is a set of services provided by a group of networked bank branches. Bank customers may access their funds and perform other simple transactions from any of the member branch ofces. The major issue in core banking is the authenticity of the customer. Due to unavoidable hacking of the databases on the internet, it is always quite difcult to trust the information on the internet. To solve this problem of authentication, we are proposing an algorithm based on image processing and visual cryptography. This paper proposes a technique of processing the signature of a customer and then dividing it into shares. Total number of shares to be created is depending on the scheme chosen by the bank.…
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An Algorithm to Automatically Generate Schedule for School Lectures Using a Heuristic Approach

Web | Desktop Application
An Algorithm to Automatically Generate Schedule for School Lectures Using a Heuristic Approach This paper proposes a general solution for the School timetabling problem. Most heuristic proposed earlier approaches the problem from the students’ point of view. This solution, however, works from the teachers’ point of view i.e. teacher availability for a given time slot. While all the hard constraints (e.g. the availability of teachers, etc.) are resolved rigorously, the scheduling solution presented in this paper is an adaptive one, with a primary aim to solve the issue of clashes of lectures and subjects, pertaining to teachers.
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A Mixed Reality Virtual Clothes Try-On System

Web | Desktop Application
A Mixed Reality Virtual Clothes Try-On System Virtual try-on of clothes has received much attention recently due to its commercial potential. It can be used for online shopping or intelligent recommendation to narrow down the selections to a few designs and sizes. In this paper, we present a mixed reality system for 3D virtual clothes try-on that enables a user to see herself wearing virtual clothes while looking at a mirror display, without taking off her actual clothes. The user can select various virtual clothes for trying-on. The system physically simulates the selected virtual clothes on the user's body in real-time and the user can see virtual clothes fitting on the her mirror image from various angles as she moves. The major contribution of this paper is that we automatically…
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Analysis of Denial-of-Service attacks on Wireless Sensor Networks Using Simulation

Networking
Analysis of Denial-of-Service attacks on Wireless Sensor Networks Using Simulation Evaluation of Wireless Sensor Networks (WSN) for performance evaluation is a popular research area and a wealth of literature exists in this area. Denial-of-Service (DoS) attacks are recognized as one of the most serious threats due to the resources constrained property in WSN. The Zigbee model provided in OPNET 16 is suitable for modelling WSNs. This paper presents an evaluation of the impact of DoS attacks on the performances of Wireless Sensor Networks by using the OPNET modeller. Numerical results, discussions and comparisons are provided for various simulation scenarios. The results can be of great help for optimisation studies in WSN environments under DoS attacks as well as understanding the severity and critical nodes within the WSN. The effects of…
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Network Traffic Monitoring Using Intrusion Detection System

Networking
Network Traffic Monitoring Using Intrusion Detection System Security is a big issue for all networks in today’s enterprise environment. Many methods have been developed to secure the network infrastructure and communication over the Internet, among them the use of firewalls, encryption, and virtual private networks. Intrusion detection is a relatively new addition to such techniques. IDS protect a system from attack, misuse, and compromise. It can also monitor network activity. Network traffic monitoring and measurement is increasingly regarded as an essential function for understanding and improving the performance and security of our cyber infrastructure.
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Analyzing Network Traffic To Detect Self-Decrypting Exploit Code

Networking
Analyzing Network Traffic To Detect Self-Decrypting Exploit Code ABSTRACT Remotely-launched software exploits are a common way for attackers to intrude into vulnerable computer systems. As detection techniques improve, remote exploitation techniques are also evolving. Recent techniques for evasion of exploit detection include polymorphism (code encryption) and metamorphism (code obfuscation). This paper addresses the problem of detecting in network traffic polymorphic remote exploits that are encrypted, and that self-decrypt before launching the intrusion. Such exploits pose a great challenge to existing malware detection techniques, partly due to the non-obvious starting location of the exploit code in the network payload.
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Genetic algorithm for energy efficient QoS Multicast Routing

Networking
Genetic algorithm for energy efficient QoS Multicast Routing The consideration of energy consumption in wireless ad hoc networks prevents the problem of the network exhausting batteries, thus partitioning the entire network. Power-aware multicasting is proposed to reduce the power consumption. This letter presents an energy-efficient genetic algorithm mechanism to resolve quality of service (QoS) multicast routing problem, which is NP-complete. The proposed genetic algorithm depends on bounded end-to-end delay and minimum energy cost of the multicast tree. Simulation results show that the proposed algorithm is effective and efficient.
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Lightweight Sybil Attack Detection in MANETs

Networking
Lightweight Sybil Attack Detection in MANETs Fully self-organized mobile ad hoc networks (MANETs) represent complex distributed systems that may also be part of a huge complex system, such as a complex system-of-systems used for crisis management operations. Due to the complex nature of MANETs and its resource constraint nodes, there has always been a need to develop lightweight security solutions. Since MANETs require a unique, distinct, and persistent identity per node in order for their security protocols to be viable, Sybil attacks pose a serious threat to such networks. A Sybil attacker can either create more than one identity on a single physical device in order to launch a coordinated attack on the network or can switch identities in order to weaken the detection process, thereby promoting lack of accountability…
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View-invariant action recognition based on Artificial Neural Networks.

Networking
View-invariant action recognition based on Artificial Neural Networks. In this paper, a novel view invariant action recognition method based on neural network representation and recognition is proposed. The project has employed the technique mentioned and excellent results were obtained for a number of widely used font types. The technical approach followed in processing input images, detecting graphic symbols, analyzing and mapping the symbols and training the network for a set of desired Unicode characters corresponding to the input images are discussed in the subsequent sections. Even though the implementation might have some limitations in terms of functionality and robustness, the researcher is confident that it fully serves the purpose of addressing the desired objectives. The novel representation of action images is based on learning spatially related prototypes using Self Organizing…
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Lossless image compression based on data folding

Image Processing, Web | Desktop Application
Lossless image compression based on data folding The paper presents an approach for lossless image compression in spatial domain for continuous-tone images using a novel concept of image folding. The proposed method uses the property of adjacent neighbor redundancy for prediction. In this method, column folding followed by row folding is applied iteratively on the image till the image size reduces to a smaller pre-defined value. For column folding, elements of even columns are subtracted from elements of odd columns. Thereafter, row folding is applied on odd columns in a similar fashion. In row folding, even rows are subtracted from odd rows and the resultant odd rows are used for next iteration. The difference data, thus obtained, is stored in a tile format; which along with the reduced image is…
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A New Cell Counting Based Attack Against Tor.

Networking
A New Cell Counting Based Attack Against Tor. Various low-latency anonymous communication systems such as Tor and Anonymizer have been designed to provide anonymity service for users. In order to hide the communication of users, most of the anonymity systems pack the application data into equal-sized cells. Via extensive experiments on Tor, we found that the size of IP packets in the Tor network can be very dynamic because a cell is an application concept and the IP layer may repack cells. Based on this finding, we investigate a new cell-counting-based attack against Tor, which allows the attacker to confirm anonymous communication relationship among users very quickly. In this attack, by marginally varying the number of cells in the target traffic at the malicious exit onion router, the attacker can…
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A chaotic system based fragile watermarking scheme for image tamper detection

Image Processing, Web | Desktop Application
A chaotic system based fragile watermarking scheme for image tamper detection In the past few years, various fragile watermarking techniques have been proposed for image authen- tication and tamper detection. In this paper, a novel chaos based watermarking scheme for image authentication and tamper detection is proposed. Tamper localization and detection accuracy are two important aspects of the authentication watermarking schemes. Our scheme can detect any modifica- tion made to the image and can also indicate the specific locations that have been modified. To improve the security of the proposed scheme two chaotic maps are employed. Since chaotic maps are sensitive to initial values, the corresponding position relation between pixels in the watermarked image and the watermark get disturbed, which helps the watermarking scheme to withstand counterfeiting attacks. Initial values…
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Load Balancing Multipath Switching System with Flow Slice.

Networking
Load Balancing Multipath Switching System with Flow Slice. Multipath Switching systems are intensely used in state-of-the-art core routers to provide terabit or even petabit switching capacity. One of the most intractable issues in designing MPS is how to load balance traffic across its multiple paths while not disturbing the interflow packet orders. Previous packet-based solutions either suffer from delay penalties or lead to hardware complexity, hence do not scale. Flow-based hashing algorithms also perform badly due to the heavy-tailed flow-size distribution. In this paper, we develop a novel scheme, namely, Flow Slice that cuts off each flow into flow slices at every interflow interval larger than a slicing threshold and balances the load on a finer granularity. Based on the studies of tens of real Internet traces, we show that…
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Optimal Power Allocation in Multi-Relay MIMO Cooperative Networks: Theory and Algorithms.

Networking
Optimal Power Allocation in Multi-Relay MIMO Cooperative Networks: Theory and Algorithms. Cooperative networking is known to have significant potential in increasing network capacity and transmission reliability. Although there have been extensive studies on applying cooperative networking in multi-hop ad hoc networks, most works are limited to the basic three-node relay scheme and single-antenna systems. These two limitations are interconnected and both are due to a limited theoretical understanding of the optimal power allocation structure in MIMO cooperative networks (MIMO-CN). In this paper, we study the structural properties of the optimal power allocation in MIMOCN with per-node power constraints. More specifically, we show that the optimal power allocations at the source and each relay follow a matching structure in MIMO-CN. This result generalizes the power allocation result under the basic three-node…
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Linear distance coding for image classification

Image Processing, Web | Desktop Application
Linear distance coding for image classification The traditional SPM approach based on bag-of-features (BoF) requires nonlinear classifiers to achieve good image classification performance. This paper presents a simple but effective coding scheme called Locality-constrained Linear Coding (LLC) in place of the VQ coding in traditional SPM. LLC utilizes the locality constraints to project each descriptor into its local-coordinate system, and the projected coordinates are integrated by max pooling to generate the final representation. With linear classifier, the proposed approach performs remarkably better than the traditional nonlinear SPM, achieving state-of-the-art performance on several benchmarks. Compared with the sparse coding strategy [22], the objective function used by LLC has an analytical solution. In addition, the paper proposes a fast approximated LLC method by first performing a K-nearest-neighbor search and then solving a…
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Assessing the Veracity of Identity Assertions via OSNs.

Networking
Assessing the Veracity of Identity Assertions via OSNs. Anonymity is one of the main virtues of the Internet, as it protects privacy and enables users to express opinions more freely. However, anonymity hinders the assessment of the veracity of assertions that online users make about their identity attributes, such as age or profession. We propose FaceTrust, a system that uses online social networks to provide lightweight identity credentials while preserving a user’s anonymity. Face-Trust employs a game with a purpose” design to elicit the opinions of the friends of a user about the user’s self-claimed identity attributes, and uses attack-resistant trust inference to assign veracity scores to identity attribute assertions. FaceTrust provides credentials, which a user can use to corroborate his assertions. We evaluate our proposal using a live Facebook…
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Security Enhancement Scheme for Image Steganography using S-DES Technique

Image Processing
Security Enhancement Scheme for Image Steganography using S-DES Technique In today‟s information age, information sharing and transfer has increased exponentially. The information vulnerable to unauthorised access and interception, while in storage or transmission. Cryptography and Steganography are the two major techniques for secret communication. The contents of secret message are scrambled in cryptography, where as in steganography the secret message is embedded into the cover medium. This paper presents a new generalized model by combining cryptographic and steganographic Technique. These two techniques encrypt the data as well as hide the encrypted data in another medium so the fact that a message being sent is concealed. In cryptography we are using Simplified Data Encryption Standard (S-DES) algorithm to encrypt secret message and then alteration component method is used to hide encrypted…
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Handling Multiple Failures in IP Networks through Localized On-Demand Link State Routing

Networking
Handling Multiple Failures in IP Networks through Localized On-Demand Link State Routing It has been observed that transient failures are fairly common in IP backbone networks and there have been several proposals based on local rerouting to provide high network availability despite failures. While most of these proposals are effective in handling single failures, they either cause loops or drop packets in the case of multiple independent failures. To ensure forwarding continuity even with multiple failures, we propose Localized On-demand Link State (LOLS) routing. Under LOLS, each packet carries a blacklist, which is a minimal set of failed links encountered along its path, and the next hop is determined by excluding the blacklisted links. We show that the blacklist can be reset when the packet makes forward progress towards the…
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FireCol: A Collaborative Protection Network for the Detection of Flooding DDoS Attacks

Networking
FireCol: A Collaborative Protection Network for the Detection of Flooding DDoS Attacks Distributed denial-of-service (DDoS) attacks remain a major security problem, the mitigation of which is very hard especially when it comes to highly distributed botnet-based attacks. The early discovery of these attacks, although challenging, is necessary to protect end-users as well as the expensive network infrastructure resources. In this paper, we address the problem of DDoS attacks and present the theoretical foundation, architecture, and algorithms of FireCol. The core of FireCol is composed of intrusion prevention systems (IPSs) located at the Internet service providers (ISPs) level. The IPSs form virtual protection rings around the hosts to defend and collaborate by exchanging selected traffic information. The evaluation of FireCol using extensive simulations and a real dataset is presented, showing FireCol…
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Robust Watermarking of Compressed and Encrypted JPEG2000 Images

Image Processing, Web | Desktop Application
Robust Watermarking of Compressed and Encrypted JPEG2000 Images Digital asset management systems (DAMS) generally handle media data in a compressed and encrypted form. It is sometimes necessary to watermark these compressed encrypted media items in the compressed-encrypted domain itself for tamper detection or ownership declaration or copyright management purposes. It is a challenge to watermark these compressed encrypted streams as the compression process would have packed the information of raw media into a low number of bits and encryption would have randomized the compressed bit stream. Attempting to watermark such a randomized bit stream can cause a dramatic degradation of the media quality. Thus it is necessary to choose an encryption scheme that is both secure and will allow watermarking in a predictable manner in the compressed encrypted domain. In…
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Image compression and decompression using adaptive interpolation

Image Processing, Web | Desktop Application
Image compression and decompression using adaptive interpolation A simple and fast lossy compression and decompression algorithm for digital images is proposed. The method offers varying compression ratios (depending on dimensions of the image) and the acquired decompressed image is close to the original one. A selectable tradeoff between storage size and image quality is allowed,making it possible to adjust degree of compression. Compared to JPEG, it provides us better compression ratio. The suggested method does not restrict itself to any particular type of image.
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Participatory Privacy: Enabling Privacy in Participatory Sensing

Networking
Participatory Privacy: Enabling Privacy in Participatory Sensing Participatory Sensing is an emerging computing paradigm that enables the distributed collection of data by self-selected participants. It allows the increasing number of mobile phone users to share local knowledge acquired by their sensor-equipped devices, e.g., to monitor temperature, pollution level or consumer pricing information. While research initiatives and prototypes proliferate, their real-world impact is often bounded to comprehensive user participation. If users have no incentive, or feel that their privacy might be endangered, it is likely that they will not participate. In this article, we focus on privacy protection in Participatory Sensing and introduce a suitable privacy-enhanced infrastructure. First, we provide a set of definitions of privacy requirements for both data producers (i.e., users providing sensed information) and consumers (i.e., applications accessing…
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A Fast Re-Route Method

Networking
A Fast Re-Route Method We present a method to find an alternate path, after a link failure, from a source node to a destination node, before the Interior Gateway Protocol (e.g., OSPF or IS-IS) has had a chance to reconverge in response to the failure. The target application is a small (up to tens of nodes) regional access subnetwork of a service provider’s network, which is a typical access scale encountered in practice. We illustrate the method and prove that it will find a path if one exists.
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A Query Formulation Language for the data web

Data mining
A Query Formulation Language for the data web We present a query formulation language called MashQL in order to easily query and fuse structured data on the web. The main novelty of MashQL is that it allows people with limited IT-skills to explore and query one or multiple data sources without prior knowledge about the schema, structure, vocabulary, or any technical details of these sources. More importantly, to be robust and cover most cases in practice, we do not assume that a data source should have -an offline or inline- schema. This poses several language-design and performance complexities that we fundamentally tackle. To illustrate the query formulation power of MashQL, and without loss of generality, we chose the Data Web scenario. We also chose querying RDF, as it is the…
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Optimum Relay Selection for Energy-Efficient Cooperative Ad Hoc Networks

Networking
Optimum Relay Selection for Energy-Efficient Cooperative Ad Hoc Networks The Cooperative Communication (CC) is a technology that allows multiple nodes to simultaneously transmit the same data. It can save power and extend transmission coverage. However, prior research work on topology control considers CC only in the aspect of energy saving, not that of coverage extension. We identify the challenges in the development of a centralized topology control scheme, named Cooperative Bridges, which reduces transmission power of nodes as well as increases network connectivity. Prior research on topology control with CC only focuses on maintaining the network connectivity, minimizing the transmission power of each node, whereas ignores the energy efficiency of paths in constructed topologies. This may cause inefficient routes and hurt the overall network performance in cooperative ad hoc networks.…
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Efficient and Discovery of Patterns in Sequence Data Sets.

Data mining, Web | Desktop Application
Efficient and Discovery of Patterns in Sequence Data Sets. Existing sequence mining algorithms mostly focus on mining for subsequences. However, a large class of applications, such as biological DNA and protein motif mining, require efficient mining of “approximate” patterns that are contiguous. The few existing algorithms that can be applied to find such contiguous approximate pattern mining have drawbacks like poor scalability, lack of guarantees in finding the pattern, and difficulty in adapting to other applications. In this paper, we present a new algorithm called Flexible and Accurate Motif DEtector (FLAME). FLAME is a flexible suffix-tree-based algorithm that can be used to find frequent patterns with a variety of definitions of motif (pattern) models. It is also accurate, as it always finds the pattern if it exists. Using both real…
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Detecting and Resolving Firewall Policy Anomalies

Networking
Detecting and Resolving Firewall Policy Anomalies As the network dramatically extended security considered as major issue in networks. There are many methods to increase the network security at the moment such as encryption, VPN, firewall etc. but all of these are too static to give an effective protection against attack and counter attack. We use data mining algorithm and apply it to the anomaly detection problem. In this work our aim to use data mining techniques including classification tree and support vector machines for anomaly detection. The result of experiments shows that the algorithm C4.5 has greater capability than SVM in detecting network anomaly and false alarm rate by using 1999 KDD cup data.
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Detecting and Resolving Firewall Policy Anomalies

Networking
Detecting and Resolving Firewall Policy Anomalies As the network dramatically extended security considered as major issue in networks. There are many methods to increase the network security at the moment such as encryption, VPN, firewall etc. but all of these are too static to give an effective protection against attack and counter attack. We use data mining algorithm and apply it to the anomaly detection problem. In this work our aim to use data mining techniques including classification tree and support vector machines for anomaly detection. The result of experiments shows that the algorithm C4.5 has greater capability than SVM in detecting network anomaly and false alarm rate by using 1999 KDD cup data.
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Denial of Service Defense through Web Referral

Networking
Denial of Service Defense through Web Referral The web is a complicated graph, with millions of websites interlinked together. In this paper, we propose to use this web sitegraph structure to mitigate flooding attacks on a website, using a new web referral architecture for privileged service (?WRAPS?). WRAPS allows a legitimate client to obtain a privilegeURL through a click on a referral hypherlink, from a website trusted by the target website. Using that URL, the client can get privileged access to the target website in a manner that is far less vulnerable to a DDoS flooding attack. WRAPS does not require changes to web client software and is extremely lightweight for referrer websites, which eases its deployment. The massive scale of the web sitegraph could deter attempts to isolate a…
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Mining Web Graphs for Recommendations.

Data mining, Web | Desktop Application
Mining Web Graphs for Recommendations. As the exponential explosion of various contents generated on the Web, Recommendation techniques have become increasingly indispensable. Innumerable different kinds of recommendations are made on the Web every day, including music, images, books recommendations, query suggestions, etc. No matter what types of data sources are used for the recommendations, essentially these data sources can be modeled in the form of graphs. In this paper, aiming at providing a general framework on mining Web graphs for recommendations, (1) we first propose a novel diffusion method which propagates similarities between different recommendations; (2) then we illustrate how to generalize different recommendation problems into our graph diffusion framework. The proposed framework can be utilized in many recommendation tasks on the World Wide Web, including query suggestions, image recommendations,…
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Improving Aggregate Recommendation Diversity Using Ranking-Based Techniques

Data mining, Web | Desktop Application
Improving Aggregate Recommendation Diversity Using Ranking-Based Techniques Recommender systems are becoming increasingly important to individual users and businesses for providing personalized recommendations. However, while the majority of algorithms proposed in recommender systems literature have focused on improving recommendation accuracy, other important aspects of recommendation quality, such as the diversity of recommendations, have often been overlooked. In this paper, we introduce and explore a number of item ranking techniques that can generate recommendations that have substantially higher aggregate diversity across all users while maintaining comparable levels of recommendation accuracy. Comprehensive empirical evaluation consistently shows the diversity gains of the proposed techniques using several real-world rating datasets and different rating prediction algorithms.
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Predicting missing items in shopping cart using fast algorithm

Data mining, Web | Desktop Application
Predicting missing items in shopping cart using fast algorithm Prediction in shopping cart uses partial information about the contents of a shopping cart for the prediction of what else the customer is likely to buy. In order to reduce the rule mining cost, a fast algorithm generating frequent itemsets without generating candidate itemsets is proposed. The algorithm uses Boolean vector with relational AND operation to discover frequent itemsets and generate the association rule. Association rules are used to identify relationships among a set of items in database. Initially Boolean Matrix is generated by transforming the database into Boolean values. The frequent itemsets are generated from the Boolean matrix. Then association rules are to generated from the already generated frequent itemsets. The association rules generated form the basis for prediction. The…
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A Threshold-based Similarity Measure for Duplicate Detection

Data mining, Web | Desktop Application
A Threshold-based Similarity Measure for Duplicate Detection In order to extract beneficial information and recognize a particular pattern from huge data stored in different databases with different formats, data integration is essential. However the problem that arises here is that data integration may lead to duplication. In other words, due to the availability of data in different formats, there might be some records which refer to the same entity. Duplicate detection or record linkage is a technique which is used to detect and match duplicate records which are generated in data integration process. Most approaches concentrated on string similarity measures for comparing records. However, they fail to identify records which share the semantic information. So, in this study, a thresholdbased method which takes into account both string and semantic similarity…
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Efficient Multi-dimensional Fuzzy Search for Personal Information Management Systems

Data mining, Web | Desktop Application
Efficient Multi-dimensional Fuzzy Search for Personal Information Management Systems With the explosion in the amount of semi-structured data users access and store in personal information management systems, there is a critical need for powerful search tools to retrieve often very heterogeneous data in a simple and efficient way. Existing tools typically support some IR-style ranking on the textual part of the query, but only consider structure (e.g., file directory) and metadata (e.g., date, file type) as filtering conditions. We propose a novel multi-dimensional search approach that allows users to perform fuzzy searches for structure and metadata conditions in addition to keyword conditions. Our techniques individually score each dimension and integrate the three dimension scores into a meaningful unified score. We also design indexes and algorithms to efficiently identify the most…
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Enabling Multilevel Trust in Privacy Preserving Data Mining

Data mining, Web | Desktop Application
Enabling Multilevel Trust in Privacy Preserving Data Mining Privacy Preserving Data Mining (PPDM) addresses the problem of developing accurate models about aggregated data without access to precise information in individual data record. A widely studied perturbation-based PPDM approach introduces random perturbation to individual values to preserve privacy before data are published. Previous solutions of this approach are limited in their tacit assumption of single-level trust on data miners. In this work, we relax this assumption and expand the scope of perturbation-based PPDM to Multilevel Trust (MLT-PPDM). In our setting, the more trusted a data miner is, the less perturbed copy of the data it can access. Under this setting, a malicious data miner may have access to differently perturbed copies of the same data through various means, and may combine…
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Slicing A New Approach to Privacy Preserving Data Publishing.

Data mining, Security and Encryption, Web | Desktop Application
Slicing A New Approach to Privacy Preserving Data Publishing. Several anonymization techniques, such as generalization and bucketization, have been designed for privacy preserving microdata publishing. Recent work has shown that general- ization loses considerable amount of information, especially for high-dimensional data. Bucketization, on the other hand, does not prevent membership disclosure and does not apply for data that do not have a clear separation between quasi- identifying attributes and sensitive attributes.
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Advance Mining of Temporal High Utility Itemset

Data mining, Web | Desktop Application
Advance Mining of Temporal High Utility Itemset The stock market domain is a dynamic and unpredictable environment. Traditional techniques, such as fundamental and technical analysis can provide investors with some tools for managing their stocks and predicting their prices. However, these techniques cannot discover all the possible relations between stocks and thus there is a need for a different approach that will provide a deeper kind of analysis. Data mining can be used extensively in the financial markets and help in stock-price forecasting. Therefore, we propose in this paper a portfolio management solution with business intelligence characteristics. We know that the temporal high utility itemsets are the itemsets with support larger than a pre-specified threshold in current time window of data stream. Discovery of temporal high utility itemsets is an…
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A Framework for Personal Mobile Commerce Pattern Mining and Prediction

Data mining, Web | Desktop Application
A Framework for Personal Mobile Commerce Pattern Mining and Prediction In many applications, including location based services, queries may not be precise. In this paper, we study the problem of efficiently computing range aggregates in a multidimensional space when the query location is uncertain. Specifically, for a query point Q whose location is uncertain and a set S of points in a multi- dimensional space, we want to calculate the aggregate (e.g., count, average and sum) over the subset S_ of S such that for each p ∈ S_, Q has at least probability θ within the distance γ to p. We propose novel, efficient techniques to solve the problem following the filtering-and-verification paradigm. In particular, two novel filtering techniques are proposed to effectively and efficiently remove data points from…
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Investigation and Analysis of New Approach of Intelligent Semantic Web Search Engines

Data mining, Web | Desktop Application
Investigation and Analysis of New Approach of Intelligent Semantic Web Search Engines As we know that www is allowing peoples to share the huge information from big database repositories. The amount of information grows billions of databases. Hence to search particular information from these huge databases we need specialized mechanism which helps to retrive that information efficiently. now days various types of search engines are available which makes information retrieving is difficult. but to provide the better solution to this proplem ,semantic web search engines are playing vital role.basically main aim of this kind of search engines is providing the required information is small time with maximum accuracy.
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Sequential Anomaly Detection in the Presence of Noise and Limited Feedback

Data mining, Web | Desktop Application
Sequential Anomaly Detection in the Presence of Noise and Limited Feedback This paper describes a methodology for detecting anomalies from sequentially observed and potentially noisy data. The proposed approach consists of two main elements: (1) filtering, or assigning a belief or likelihood to each successive measurement based upon our ability to predict it from previous noisy observations, and (2) hedging, or flagging potential anomalies by comparing the current belief against a time-varying and data-adaptive threshold. The threshold is adjusted based on the available feedback from an end user. Our algorithms, which combine universal prediction with recent work on online convex programming, do not require computing posterior distributions given all current observations and involve simple primal-dual parameter updates. At the heart of the proposed approach lie exponential-family models which can be…
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Clustering Methods in Data Mining with its Applications in High Education

Data mining, Web | Desktop Application
Clustering Methods in Data Mining with its Applications in High Education Data mining is a new technology, developing with database and artificial intelligence. It is a processing procedure of extracting credible, novel, effective and understandable patterns from database. Cluster analysis is an important data mining technique used to find data segmentation and pattern information. By clustering the data, people can obtain the data distribution, observe the character of each cluster, and make further study on particular clusters. In addition, cluster analysis usually acts as the preprocessing of other data mining operations. Therefore, cluster analysis has become a very active research topic in data mining. As the development of data mining, a number of clustering methods have been founded, The study of clustering technique from the perspective of statistics, based on…
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