Lime: Data Lineage in the Malicious Environment
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.
KeywordsData Lineage Information Leakage Oblivious Transfer Robust Watermark Data Provenance
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- 1.Chronology of data breaches, http://www.privacyrights.org/data-breach
- 2.Data breach cost, http://www.symantec.com/about/news/release/article.jsp?prid=20110308_01
- 4.Backes, M., Grimm, N., Kate, A.: Lime: Data lineage in the malicious environment (2014), http://arxiv.org/abs/1408.1076
- 5.Mascher-Kampfer, A., Stögner, H., Uhl, A.: Multiple re-watermarking scenarios. In: IWSSIP, pp. 53–56 (2006)Google Scholar
- 6.Naor, M., Pinkas, B.: Efficient oblivious transfer protocols. In: SODA, pp. 448–457 (2001)Google Scholar
- 7.Papadimitriou, P., Garcia-Molina, H.: Data leakage detection. IEEE Transactions on Knowledge and Data Engineering, 51–63 (2011)Google Scholar
- 8.Pfitzmann, B., Waidner, M.: Asymmetric fingerprinting for larger collusions. In: CCS, pp. 151–160 (1997)Google Scholar