Finding ε and δ of Traditional Disclosure Control Systems
DOI:
https://doi.org/10.1609/aaai.v38i20.30204Keywords:
GeneralAbstract
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.Downloads
Published
2024-03-24
How to Cite
Das, S., Zhu, K., Task, C., Van Hentenryck, P., & Fioretto, F. (2024). Finding ε and δ of Traditional Disclosure Control Systems. Proceedings of the AAAI Conference on Artificial Intelligence, 38(20), 22013-22020. https://doi.org/10.1609/aaai.v38i20.30204
Issue
Section
AAAI Technical Track on AI for Social Impact Track