Privacy through accountability: A computer science perspective

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Abstract

Privacy has become a significant concern in modern society as personal information about individuals is increasingly collected, used, and shared, often using digital technologies, by a wide range of organizations. To mitigate privacy concerns, organizations are required to respect privacy laws in regulated sectors (e.g., HIPAA in healthcare, GLBA in financial sector) and to adhere to self-declared privacy policies in self-regulated sectors (e.g., privacy policies of companies such as Google and Facebook in Web services). This article provides an overview of a body of work on formalizing and enforcing privacy policies. We formalize privacy policies that prescribe and proscribe flows of personal information as well as those that place restrictions on the purposes for which a governed entity may use personal information. Recognizing that traditional preventive access control and information flow control mechanisms are inadequate for enforcing such privacy policies, we develop principled accountability mechanisms that seek to encourage policy-compliant behavior by detecting policy violations, assigning blame, and punishing violators. We apply these techniques to several U.S. privacy laws and organizational privacy policies, in particular, producing the first complete logical specification and audit of all disclosure-related clauses of the HIPAA Privacy Rule. © 2014 Springer International Publishing Switzerland.

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Datta, A. (2014). Privacy through accountability: A computer science perspective. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8337 LNCS, pp. 43–49). Springer Verlag. https://doi.org/10.1007/978-3-319-04483-5_5

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