LiPISC: A Lightweight and Flexible Method for Privacy-Aware Intersection Set Computation.
Privacy-aware intersection set computation (PISC) can be modeled as secure multi-party computation. The basic idea is to compute the intersection of input sets without leaking privacy. Furthermore, PISC should be sufficiently flexible to recommend approximate intersection items. In this paper, we reveal two previously unpublished attacks against PISC, which can be used to reveal and link one input set to another input set, resulting in privacy leakage. We coin these as Set Linkage Attack and Set Reveal Attack. We then present a lightweight and flexible PISC scheme (LiPISC) and prove its security (including against Set Linkage Attack and Set Reveal Attack).
School of Computer Science, China University of Geosciences, Wuhan, Hubei, P.R. China.|Hubei Key Laboratory of Intelligent Geo-Information Processing (China University of Geosciences (Wuhan)), Wuhan, Hubei, P.R. China.
Wei
http://orcid.org/0000-0001-8590-1737
W
Ren
School of Computer Science, China University of Geosciences, Wuhan, Hubei, P.R. China.
Shiyong
S
Huang
Department of Computer Science, National Chiao Tung University, Hsinchu, Taiwan, R.O. China.
Yi
Y
Ren
School of Computer Science, China University of Geosciences, Wuhan, Hubei, P.R. China.|School of Information Technology and Mathematical Sciences, University of South Australia, Adelaide, South Australia, Australia.
Kim-Kwang Raymond
KK
Choo
D000465:Algorithms; D016494:Computer Security; D003219:Confidentiality; D008962:Models, Theoretical