2024
AAAI
AAAI 2024
Finding ε and δ of Traditional Disclosure Control Systems
Abstract
Abstract This paper analyzes the privacy of traditional Statistical Disclosure Control (SDC) systems under a differential privacy interpretation. SDCs, such as cell suppression and swapping, promise to safeguard the confidentiality of data and are routinely adopted in data analyses with profound societal and economic impacts. Through a formal analysis and empirical evaluation of demographic data from real households in the U.S., the paper shows that widely adopted SDC systems not only induce vastly larger privacy losses than classical differential privacy mechanisms, but, they may also come at a cost of larger accuracy and fairness.
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Interdisciplinary Bridge
- Artificial Intelligence and Data Science & Analytics and Security & Privacy