Lime: Data Lineage in the Malicious Environment
Michael Backes, Niklas Grimm, and Aniket Kate

TL;DR
LIME is a data lineage framework designed to track data flow across multiple entities in malicious environments, ensuring security guarantees and accountability through novel protocols based on cryptographic primitives.
Contribution
The paper introduces a generic data lineage framework with a novel accountable transfer protocol that operates securely in malicious environments, combining watermarking, signatures, and oblivious transfer.
Findings
Protocol is practical based on experimental results
Provides security guarantees for data ownership and transfer
Effectively identifies guilty entities in data leaks
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 and analyze a novel accountable data transfer protocol between two entities within a malicious environment by building upon…
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Taxonomy
TopicsAdvanced Steganography and Watermarking Techniques · Internet Traffic Analysis and Secure E-voting · Cryptography and Data Security
