Lime: Data lineage in the malicious environment

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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 smartphone 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 a novel accountable data transfer protocol between two entities within a malicious environment by building upon oblivious transfer, robust watermarking, and signature primitives.

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Backes, M., Grimm, N., & Kate, A. (2014). Lime: Data lineage in the malicious environment. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8743, 183–187. https://doi.org/10.1007/978-3-319-11851-2_13

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