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Privacy Through Accountability

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Privacy through accountability refers to the principle that entities that hold personal information about individuals are accountable for adopting measures that protect the privacy of the data subjects [1]. This article focuses on computational treatments of this principle. This research area has produced precise definitions of privacy properties and computational accountability mechanisms to aid in their enforcement.

Formally, privacy properties impose restrictions on personal information flows. Information flow types encompass context-specific direct flows (e.g., transfer of health information from a hospital to an insurance company) [2,3,4], implicit flows (e.g., the use of users’ location in a web advertising system) [5], and flows of noisy statistics from databases of personal information (e.g., the use of customers’ ratings to recommend movies) [6]. The restrictions on these types of information flow include role-based restrictions (e.g., permitting certain types of...

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Recommended Reading

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Correspondence to Anupam Datta .

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Datta, A. (2017). Privacy Through Accountability. In: Liu, L., Özsu, M. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4899-7993-3_80601-2

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  • DOI: https://doi.org/10.1007/978-1-4899-7993-3_80601-2

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  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4899-7993-3

  • Online ISBN: 978-1-4899-7993-3

  • eBook Packages: Springer Reference Computer SciencesReference Module Computer Science and Engineering

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