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AuthorLin, Jiaping
AuthorNiu, Jianwei
AuthorLiu, Xuefeng
AuthorGuizani, Mohsen
Available date2022-11-02T20:30:32Z
Publication Date2021-05-01
Publication NameIEEE Transactions on Mobile Computing
Identifierhttp://dx.doi.org/10.1109/TMC.2020.2972001
CitationLin, J., Niu, J., Liu, X., & Guizani, M. (2020). Protecting your shopping preference with differential privacy. IEEE Transactions on Mobile Computing, 20(5), 1965-1978.‏
ISSN15361233
URIhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85103935811&origin=inward
URIhttp://hdl.handle.net/10576/35769
AbstractOnline banks may disclose consumers' shopping preferences due to various attacks. With differential privacy, each consumer can disturb his consumption amount locally before sending it to online banks. However, directly applying differential privacy in online banks will incur problems in reality because existing differential privacy schemes do not consider handling the noise boundary problem. In this paper, we propose an Optimized Differential prIvate Online tRansaction scheme (O-DIOR) for online banks to set boundaries of consumption amounts with added noises. We then revise O-DIOR to design a RO-DIOR scheme to select different boundaries while satisfying the differential privacy definition. Moreover, we provide in-depth theoretical analysis to prove that our schemes are capable to satisfy the differential privacy constraint. Finally, to evaluate the effectiveness, we have implemented our schemes in mobile payment experiments. Experimental results illustrate that the relevance between the consumption amount and online bank amount is reduced significantly, and the privacy losses are less than 0.5 in terms of mutual information.
SponsorThis work was supported by the National Natural Science Foundation of China (61572060, 61772060, 61728201) and CERNET Innovation Project (NGII20170315).
Languageen
PublisherInstitute of Electrical and Electronics Engineers Inc.
SubjectDifferential privacy
noise boundary
online bank
shopping preference protection
TitleProtecting Your Shopping Preference with Differential Privacy
TypeArticle
Pagination1965-1978
Issue Number5
Volume Number20
dc.accessType Abstract Only


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