A Game Theoretic Framework for Analyzing Re-Identification Risk
Given the potential wealth of insights in personal data the big databases can provide, many organizations aim to share data while protecting privacy by sharing de-identified data, but are concerned because various demonstrations show such data can be re-identified. Yet these investigations focus on how attacks can be perpetrated, not the likelihood they will be realized. This paper introduces a game theoretic framework that enables a publisher to balance re-identification risk with the value of
Record details
Published: 25 March 2015
Source: OpenAlex
Category: Research
Topics: Privacy · Finance, VC & PE
Retrieved: 14 July 2026
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How to cite this record
ethics.ai (25 March 2015), “A Game Theoretic Framework for Analyzing Re-Identification Risk,” evidence record 7852, https://ethics.ai/record/7852 (originally published by OpenAlex).
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