Data Leakage Detection

In the business, sometimes sensitive data must be handed over to trusted third parties. So some companies distribute their data to trusted third parties. These companies (data distributer) found their some of the data in unauthorized place (e.g., on the web or somebody’s laptop). The distributor understands that the leaked data came from one or more agents. Our goal is to detect which agent leaks that data and provide the security to that data. When the distributor’s sensitive data have been leaked by agents, and to identify the agent that leaked the data. 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. The Main Aim of the system can be given as follows:Identify data leakages from distributed data using some data allocation strategies and find out the fake agent who leak that data. Improve probability of finding out fake agent and provide

[1]  Jianmin Wang,et al.  An Improved Algorithm to Watermark Numeric Relational Data , 2005, WISA.

[2]  M. Atallah,et al.  Watermarking Relational Databases , 2002 .

[3]  Hector Garcia-Molina,et al.  Data Leakage Detection , 2011, IEEE Transactions on Knowledge and Data Engineering.

[4]  Hector Garcia-Molina,et al.  Privacy, Preservation and Performance: The 3 P's of Distributed Data Management , 2008, 2008 11th IEEE High Assurance Systems Engineering Symposium.

[5]  Panos M. Pardalos,et al.  Quadratic programming with one negative eigenvalue is NP-hard , 1991, J. Glob. Optim..

[6]  Frank Boland,et al.  Watermarking digital images for copyright protection , 1995 .

[7]  V. N. Murty Counting the Integer Solutions of a Linear Equation with Unit Coefficients , 1981 .

[8]  Radu Sion,et al.  Rights protection for relational data , 2003, IEEE Transactions on Knowledge and Data Engineering.

[9]  Jennifer Widom,et al.  Lineage tracing for general data warehouse transformations , 2003, The VLDB Journal.

[10]  Richard Fromm,et al.  Digital Music Distribution and Audio Watermarking , 2007 .

[11]  W. J. Dowling,et al.  Watermarking digital images for copyright protection , 1996 .

[12]  Sanjeev Khanna,et al.  Why and Where: A Characterization of Data Provenance , 2001, ICDT.

[13]  Rakesh Agrawal,et al.  Watermarking Relational Databases , 2002, Very Large Data Bases Conference.

[14]  Rajeev Motwani,et al.  Towards robustness in query auditing , 2006, VLDB.

[15]  Peter Buneman,et al.  Provenance in databases , 2009, SIGMOD '07.

[16]  Sabrina De Capitani di Vimercati,et al.  An algebra for composing access control policies , 2002, TSEC.

[17]  Sushil Jajodia,et al.  Fingerprinting relational databases: schemes and specialties , 2005, IEEE Transactions on Dependable and Secure Computing.

[18]  Sushil Jajodia,et al.  Flexible support for multiple access control policies , 2001, TODS.

[19]  Lior Rokach,et al.  A Survey of Data Leakage Detection and Prevention Solutions , 2012, SpringerBriefs in Computer Science.

[20]  Latanya Sweeney,et al.  Achieving k-Anonymity Privacy Protection Using Generalization and Suppression , 2002, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[21]  Bernd Girod,et al.  Watermarking of uncompressed and compressed video , 1998, Signal Process..