📞 +91-7667918914 | ✉️ iarjset@gmail.com
International Advanced Research Journal in Science, Engineering and Technology
International Advanced Research Journal in Science, Engineering and Technology A Monthly Peer-Reviewed Multidisciplinary Journal
ISSN Online 2393-8021ISSN Print 2394-1588Since 2014
IARJSET aligns to the suggestive parameters by the latest University Grants Commission (UGC) for peer-reviewed journals, committed to promoting research excellence, ethical publishing practices, and a global scholarly impact.
← Back to Archives

Data Leakage Detection

Mr. Sagar Ravindra Dalvi, Ms. Shamika Rajendra Khatu

👁 3 views📥 0 downloads
Share: 𝕏 f in
Abstract: A data distributor has given sensitive data to a set of supposedly trusted agents (third parties). Some of the data is leaked and found in an unauthorized place (e.g., on the web or somebody's laptop). 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. Data allocation strategies (across the agents) that improve the probability of identifying leakages has been proposed. These methods do not rely on alterations of the released data (e.g., watermarks). In some cases distributor can also inject "realistic but fake" data records to further improve our chances of detecting leakage and identifying the guilty party. Keywords: Guilty agent, data distributor, fake object, data leakage.

How to Cite:

[1] Mr. Sagar Ravindra Dalvi, Ms. Shamika Rajendra Khatu, “Data Leakage Detection,” International Advanced Research Journal in Science, Engineering and Technology (IARJSET), DOI: 10.17148/IARJSET/NCIARCSE.2017.48

Creative Commons License This work is licensed under a Creative Commons Attribution 4.0 International License.