IEEE 2015 Dot Net Projects

A refinement algorithm for rank aggregation over crowd sourced comparison data

  Extracting ranking from pairwise comparison data has been very popular these days especially due to the huge source of comparison data available in the Internet. One of the many ways to collect a large amount of data from ordinary users is crowd sourcing. One example is reCaptcha, which converts scanned text images into text [...]

Anti-phishing using Hadoop-framework

  Phishing is an activity that is carried out online inorder to steal the identity of the users online such as their user IDs, passwords and credit card details. Unaware online users easily fall for these phishing web pages because of their high similarities to the real ones. Detecting & Identifying fake websites is a [...]

Max-Confidence Boosting With Uncertainty for Visual Tracking

  The challenges in visual tracking call for a method which can reliably recognize the subject of interests in an environment, where the appearance of both the background and the foreground change with time. Many existing studies model this problem as tracking by classification with online updating of the classification models, however, most of them [...]

On Local Prediction Based Reversible Watermarking

  The use of local prediction in difference expansion reversible watermarking provides very good results, but at the cost of computing for each pixel a least square predictor in a square block centered on the pixel. This correspondence investigates the reduction of the mathematical complexity by computing distinct predictors not for pixels, but for groups [...]

An Efficient and Trustworthy P2P and Social Network Integrated File Sharing System

  Efficient and trustworthy file querying is important to the overall performance of peer-to-peer (P2P) file sharing systems. Emerging methods are beginning to address this challenge by exploiting online social networks (OSNs). However, current OSN-based methods simply cluster common-interest nodes for high efficiency or limit the interaction between social friends for high trustworthiness, which provides [...]

A Similarity-Based Learning Algorithm Using Distance Transformation

  Numerous theories and algorithms have been developed to solve vectorial data learning problems by searching for the hypothesis that best fits the observed training sample. However, many real-world applications involve samples that are not described as feature vectors, but as (dis)similarity data. Converting vectorial data into (dis)similarity data is more easily performed than converting [...]

Risk Aware Query Replacement Approach for Secure Databases Performance Management

  Large amount of data and increased demand to extract, analyze and derive knowledge from data are impairing nowadays performance of enterprise mission-critical systems such as databases. For databases, the challenging problem is to manage complex and sometimes non-optimized queries executed on enormous data sets stored across several tables. This generally results in increased query [...]

An Efficient Framework for Generating Storyline Visualizations from Streaming Data

  This paper presents a novel framework for applying storyline visualizations to streaming data. The framework includes three components: a new data management scheme for processing and storing the incoming data, a layout construction algorithm specifically designed for incrementally generating storylines from streaming data, and a layout refinement algorithm for improving the legibility of the [...]

Higher LSB Optimize Data Hiding Mechanism on Encrypted Image

  Now a day’s to keep up secrecy and confidentiality of an information could be a vivacious field with 2 totally different approaches being followed, the primary being encrypting the pictures through cryptography algorithms victimization keys, the opposite approach involves concealing knowledge victimization data concealing algorithmic program to keep up the pictures secrecy. A content [...]

Keyword Extraction and Clustering for Document Recommendation in Conversations

This paper addresses the problem of keyword extraction from conversations, with the goal of using these keywords to retrieve, for each short conversation fragment, a small number of potentially relevant documents, which can be recommended to participants. However, even a short fragment contains a variety of words, which are potentially related to several topics; moreover, [...]