title: Small sum privacy and large sum utility in data publishing.
abstract: While the study of privacy preserving data publishing has drawn a lot of interest, some recent work has shown that existing mechanisms do not limit all inferences about individuals. This paper is a positive note in response to this finding. We point out that not all inference attacks should be countered, in contrast to all existing works known to us, and based on this we propose a model called SPLU. This model protects sensitive information, by which we refer to answers for aggregate queries with small sums, while queries with large sums are answered with higher accuracy. Using SPLU, we introduce a sanitization algorithm to protect data while maintaining high data utility for queries with large sums. Empirical results show that our method behaves as desired.
authors.affiliation: Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong. Electronic address: adafu@cse.cuhk.edu.hk.
authors.forename: Ada Wai-Chee
authors.initials: AW
authors.lastname: Fu
authors.affiliation: Department of Computer Science, Simon Fraser University, Canada. Electronic address: wangk@cs.sfu.ca.
authors.forename: Ke
authors.initials: K
authors.lastname: Wang
authors.affiliation: Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Hong Kong. Electronic address: raywong@cse.ust.hk.
authors.forename: Raymond Chi-Wing
authors.initials: RC
authors.lastname: Wong
authors.affiliation: Department of Computer Science, University of Illinois at Urbana-Champaign, USA. Electronic address: jwang@cse.cuhk.edu.hk.
authors.forename: Jia
authors.initials: J
authors.lastname: Wang
authors.affiliation: Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Hong Kong. Electronic address: minhaojiang@gmail.com.
authors.forename: Minhao
authors.initials: M
authors.lastname: Jiang
mesh_terms: D020407:Internet; D008962:Models, Theoretical; D018907:Privacy; D011643:Publishing
keywords: Inference attacks; Privacy preserving data publishing; Privacy versus utility