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Computer Science > Cryptography and Security

Title: From Closed-world Enforcement to Open-world Assessment of Privacy

Abstract: In this paper, we develop a user-centric privacy framework for quantitatively assessing the exposure of personal information in open settings. Our formalization addresses key-challenges posed by such open settings, such as the unstructured dissemination of heterogeneous information and the necessity of user- and context-dependent privacy requirements. We propose a new definition of information sensitivity derived from our formalization of privacy requirements, and, as a sanity check, show that hard non-disclosure guarantees are impossible to achieve in open settings.
After that, we provide an instantiation of our framework to address the identity disclosure problem, leading to the novel notion of d-convergence. d-convergence is based on indistinguishability of entities and it bounds the likelihood with which an adversary successfully links two profiles of the same user across online communities.
Finally, we provide a large-scale evaluation of our framework on a collection of 15 million comments collected from the Online Social Network Reddit. Our evaluation validates the notion of d-convergence for assessing the linkability of entities in our data set and provides deeper insights into the data set's structure.
Comments: embedded d-convergences into larger theory
Subjects: Cryptography and Security (cs.CR)
Cite as: arXiv:1502.03346 [cs.CR]
  (or arXiv:1502.03346v4 [cs.CR] for this version)

Submission history

From: Praveen Manoharan [view email]
[v1] Wed, 11 Feb 2015 15:54:35 GMT (3242kb,D)
[v2] Mon, 13 Apr 2015 17:31:06 GMT (3248kb,D)
[v3] Tue, 21 Jul 2015 11:07:27 GMT (3233kb,D)
[v4] Thu, 12 May 2016 15:26:43 GMT (292kb,D)