The Rapid Development Of Online Reputation Systems

Online reputation systems are playing increasingly important roles in influencing people’s online purchasing/downloading decisions. The manipulations against such systems which overly inflate or deflate reputation scores of online items are evolving rapidly. For example, for just $9.99, a video on YouTube could receive 30 “I like” ratings or 30 real …

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Filtering Infromation and Short text Classification in OSN

ONLINE Social Networks (OSNs) are today one of the most popular interactive medium to communicate, share, and disseminate a considerable amount of human life information. Daily and continuous communications imply the exchange of several types of content, including free text, image, audio, and video data. According to Facebook statistics1 average …

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DPMFP: Feature Partitions based document clustering

This paper proposes a DPMFP method for document clustering. This paper attempt to group documents into an optimal number of clusters while the number of clusters K is discovered automatically. Develop a Dirichlet Process Mixture (DPM) model to partition documents. There are two algorithms to infer DPM parameters, in particular, …

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Retrieve Content From Remote Servers Via Uplink query processing

THE processing and storage capabilities of mobile consumer devices are becoming increasingly powerful. A gamut of new mobile applications has thus emerged for providing a better quality of experience for the end users. A class of such applications commonly referred to as mobile augmented reality includes ones that enable delivery …

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Task Scheduling and Software Project Planning Using ACO

The rapid development of the software industry, software companies are now facing a highly competitive market. To succeed, companies have to make efficient project plans to reduce the cost of software construction It is in medium to large-scale projects, the problem of project planning is very complex and challenging. For …

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Improving Classification Accuracy

This paper considers the notion of identifying subsets of critical data instances in data sets. Critical nuggets of information can take the following form during classification tasks: small subsets of data instances that lie very close to the class boundary and are sensitive to small changes in attribute values, such …

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Decentralized, Key-Based Caching And Checking System To Catch Cloned Nodes

In this paper, we propose two novel node clone detection protocols with different tradeoffs on network conditions and performance. The first one is based on a distributed hash table (DHT), by which a fully decentralized, key-based caching and checking system is constructed to catch cloned nodes effectively. The protocol performance …

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SECURE COVERAGE OF LARGE SCALE WIRELESS SENSOR NETWORK

We proposed, in this work, a scalable key management scheme which ensures a good secure coverage of large scale WSN with a low key storage overhead and a good network resiliency.One of the main concerns when designing a key management scheme is the network scalability. Indeed, the protocol should support …

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Enhanced Adaptive ACKnowledgment to detect Secure Intrusion in for MANETs

In this paper, we propose and implement a new intrusion-detection system named Enhanced Adaptive ACKnowledgment (EAACK) specially designed for MANETs. Compared to contemporary approaches, EAACK demonstrates higher malicious- behavior-detection rates in certain circumstances while does not greatly affect the network performances. The migration to wireless network from wired network has …

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Secure Two-Party Differentially Private Data Release for Vertically-Partitioned Data

Privacy-preserving data publishing addresses the problem of disclosing sensitive data when mining for useful information. Among the existing privacy models, ε-differential privacy provides one of the strongest privacy guarantees. In this paper, we address the problem of private data publishing, where different attributes for the same set of individuals are …

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A Fast Clustering-Based Feature Subset Selection Algorithm for High-Dimensional Data

Feature selection involves identifying a subset of the most useful features that produces compatible results as the original entire set of features. A feature selection algorithm may be evaluated from both the efficiency and effectiveness points of view. While the efficiency concerns the time required to find a subset of …

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A generic framework for constructing encounter-based social Networks

In this paper, we explore the functional and security requirements for these new systems, such as availability, security, and privacy, and present several design options for building secure encounter-based social networks. To highlight these challenges we examine one recently proposed encounter-based social network design and compare it to a set …

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