International Journal of Computer
Trends and Technology

Research Article | Open Access | Download PDF

Volume 3 | Issue 4 | Year 2012 | Article Id. IJCTT-V3I4P106 | DOI : https://doi.org/10.14445/22312803/IJCTT-V3I4P106

Development of Data leakage Detection Using Data Allocation Strategies

Polisetty Sevani Kumari, Kavidi Venkata Mutyalu

Citation :

Polisetty Sevani Kumari, Kavidi Venkata Mutyalu, "Development of Data leakage Detection Using Data Allocation Strategies," International Journal of Computer Trends and Technology (IJCTT), vol. 3, no. 4, pp. 457-461, 2012. Crossref, https://doi.org/10.14445/22312803/IJCTT-V3I4P106

Abstract

A data distributor has given sensitive data to a set of supposedly trusted agents (third parties). Some of the data are leaked and found in an unauthorized place. The distributor must assess the likelihood that the leaked data came from one or more agents, as opposed to having been independently gathered by other means. We propose data allocation strategies (across the agents) that improve the probability of identifying leakages. These methods do not rely on alterations of the released data (e.g., watermarks). In some cases, we can also inject “realistic but fake” data records to further improve our chances of detecting leakage and identifying the guilty party. In previously only one agent is going to leak the data but by using allocation strategies we are going to create multiple agents. this project is possible to show in stand alone system, but now we are going to show the result dynamically using MVC architecture.

Keywords

OpenMP, Par4All, PIPS, PoCC, Polyhedral Model, Cache-Line Size, On-Chip Cache Memory.

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