Contact Project Developer Ashish D. Tiwari [astiwz@gmail.com]
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Desktop Applications Cloud Java JSP Data Mining ME-Engineering(CO/IT) BCS MCS BCA MCA MCM BSC Computer/IT MSC Computer/IT Diploma (CO/IT) IEEE-2015

Data Lineage in Malicious Environments

In this work, we present a generic data lineage framework LIME for data flow across multiple entities that take two characteristic, principal roles (i.e., owner and consumer).
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Data Lineage in Malicious Environments.

Abstract:

Intentional or unintentional leakage of confidential data is undoubtedly one of the most severe security threats that organizations face in the digital era. The threat now extends to our personal lives: a plethora of personal information is available to social networks and smart phone providers and is indirectly transferred to untrustworthy third party and fourth party applications. In this work, we present a generic data lineage framework LIME for data flow across multiple entities that take two characteristic, principal roles (i.e., owner and consumer). We define the exact security guarantees required by such a data lineage mechanism toward identification of a guilty entity, and identify the simplifying non-repudiation and honesty assumptions. We then develop and analyze a novel accountable data transfer protocol between two entities within a malicious environment by building upon oblivious transfer, robust watermarking, and signature primitives. Finally, we perform an experimental evaluation to demonstrate the practicality of our protocol and apply our framework to the important data leakage scenarios of data outsourcing and social networks. In general, we consider LIME , our lineage framework for data transfer, to be an key step towards achieving accountability by design.
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