Development of Data leakage Detection Using Data Allocation Strategies
 | International Journal of Computer Trends and Technology (IJCTT) |  |
| © - Issue 2012 by IJCTT Journal | ||
| Volume-3 Issue-4 | ||
| Year of Publication : 2012 | ||
| Authors :Polisetty Sevani Kumari, Kavidi Venkata Mutyalu |
Polisetty Sevani Kumari, Kavidi Venkata Mutyalu"Development of Data leakage Detection Using Data Allocation Strategies"International Journal of Computer Trends and Technology (IJCTT),V3(4):457-461 Issue 2012 .ISSN 2231-2803.www.ijcttjournal.org. Published by Seventh Sense Research Group.
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.
References-
[1] A.subbiah and D.M.Blough.An Approach for fault tolerant and secure data storage in collaborative Work environments.
[2].B.Mungamuru and H.Garcia-molina,”privacy,preservation and Performance: The 3 p’s of Distributed Data Management,” technical report, Stanford univ.,2008
[3] M. Atallah and s.Wagstaff. Watermarking with quadratic residues. In proc.of IS&T/SPIE Conference on Security and Watermarking of Multimedia Contents, January 1999.
[4] P. Buneman and W.-C. Tan, “Provenance in Databases,” Proc. ACM SIGMOD, pp. 1171-1173, 2007
[5] S.Katzenbeisser and F.A.peticolas,editors. Information Hiding Techniques for Steganography and Digital Watermarking. Artech House,2000.
[6] R. Agrawal and J. Kiernan, “Watermarking Relational Databases,” Proc. 28th Int’l Conf. Very Large Data Bases (VLDB ’02), VLDB Endowment, pp. 155-166, 2002.
[7] Y. Cui and J. Widom, “Lineage Tracing for General Data Warehouse Transformations,” The VLDB J., vol. 12, pp. 41-58, 2003.
KeywordsOpenMP, Par4All, PIPS, PoCC, Polyhedral Model, Cache-Line Size, On-Chip Cache Memory.