Affiliation:
1. Hong Kong University of Science and Technology, Hong Kong
Abstract
Differential privacy has garnered significant attention in recent years due to its potential in offering robust privacy protection for individual data during analysis. With the increasing volume of sensitive information being collected by organizations and analyzed through SQL queries, the development of a general-purpose query engine that is capable of supporting a broad range of queries while maintaining differential privacy has become the holy grail in privacypreserving query release. Towards this goal, this article surveys recent advances in query evaluation under differential privacy.
Publisher
Association for Computing Machinery (ACM)
Subject
Information Systems,Software
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Cited by
2 articles.
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