EVALUATE FAKE OBJECTS TO PREDICTS UNAUTHENTICATED DEVELOPERS
Journal Title: International Journal of Advanced Research in Computer Engineering & Technology(IJARCET) - Year 2012, Vol 1, Issue 4
Abstract
Abstract: Modern business activities rely on extensive email exchange. Email leakages have become widespread, and the severe damage caused by such leakages constitutes a disturbing problem for organizations. In this paper we studied the following problem: In the course of doing business, sometimes the data distributor will give sensitive data to trusted third parties. Some of the data is leaked and found in an unauthorized place. The distributor cannot blame the agent without any evidence. Current approaches can detect the hackers but the total number of evidence will be less and the organization may not be able to proceed legally for further proceedings. In this work, we implement and analyze a guilt model that detects the agents using allocation strategies without modifying the original data. Our work identifies the agent who leaked the data with enough evidence. The main focus of this paper is to distribute the sensitive data “intelligently” to agents in order to improve the chances of detecting a guilty agent with strong evidence. The objective of our work is to improve the probability of identifying leakages using Data allocation strategies across the agents and also to identify the guilty party who leaked the data by injecting “realistic but fake” data records.
Authors and Affiliations
A. Santhi Lakshmi , Prof. C. Rajendra,
Keywords
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