BibTeX:

@article{IJIRSTV1I9026,
     title={Assess Agent Guilt Model and Handling Data Allocation Strategies for Data Distribution},
     author={C Sakthivel, S Poovarasan, A Velkuppannasamy and T Karthikeyan},
     journal={International Journal for Innovative Research in Science & Technology},
     volume={1},
     number={9},
     pages={70--73},
     year={},
     url={http://www.ijirst.org/articles/IJIRSTV1I9026.pdf},
     publisher={IJIRST (International Journal for Innovative Research in Science & Technology)},
}

A data distributor has given sensitive data to a set of supposedly trusted agents (third parties). The data are 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 have independent that gathered by other means. Data allocation strategies that we proposed (across the agents) improve the probability of identifying leakages. The model doesn’t rely on alterations of the released data (e.g., watermarks). In the proposed system, injected “realistic but fake” data records to further improve the chances of detecting leakage and identifying the guilty party.

Guilt Model, Watermarking, Data distribution, Perturbation