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Student of P.V.P.P.C.O.E. Student of P.V.P.P.C.O.E. Associate Professor

By Unnati Kavali, Tejal Abhang and Mr. Vaibhav Narawade


Abstract--Some distributer or a BPO company has given sensitive data to a set of supposedly trusted companies or a set of agents (third parties). If the data distributed to third parties is found in a public/private domain then finding the guilty party is a nontrivial task to distributor. Traditionally, this leakage of data is handled by water marking technique which requires modification of data. If the watermarked copy is found at some unauthorized site then distributor can claim his ownership. To overcome the disadvantages of using watermark Data allocation strategies are used to improve the probability of identifying guilty third parties. In this project, we implement and analyze a guilt model that detects the agents using allocation strategies without modifying the original data. The guilty agent is one who leaks a portion of distributed data. The idea is to distribute the data intelligently to agents. Keywords--sensitive data; fake objects; data allocation strategies. I

Year: 2014
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