文献类型：期刊文献

英文题名：An effective approach for the protection of user commodity viewing privacy in e-commerce website

作者：Wu, Zongda[1];Shen, Shigen[1];Zhou, Haiping[1];Li, Huxiong[1];Lu, Chenglang[2];Zou, Dongdong[3]

机构：[1]Shaoxing Univ, Dept Comp Sci & Engn, Shaoxing 312000, Zhejiang, Peoples R China;[2]Zhejiang Inst Mech & Elect Engn, Hangzhou 310053, Zhejiang, Peoples R China;[3]Wenzhou Univ, Oujiang Coll, Wenzhou 325035, Zhejiang, Peoples R China

年份：2021

卷号：220

外文期刊名：KNOWLEDGE-BASED SYSTEMS

收录：SSCI(收录号：WOS:000637680300008)、SCI-EXPANDED(收录号：WOS:000637680300008)、、EI(收录号：20211210125505)、Scopus(收录号：2-s2.0-85102857686)、WOS

基金：This work is a research achievement from the Zhijiang Youth Project of Zhejiang Social Science Planning of China, and this work was supported in part by the Major Humanities and Social Sciences Research Project of Zhejiang Provincial Universities of China (No. 2021GH017), the Zhejiang Provincial Natural Science Foundation of China (Nos. LZ18F020001 and LY19F020018) and the National Natural Science Foundation of China (Nos. 61762055 and 61962029).

语种：英文

外文关键词：E-commerce website; Privacy protection; Privacy model; Information entropy

外文摘要：Along with the rapid development of network technologies, the server-side of an e-commerce website is becoming more and more untrustworthy. Thus, how to prevent the disclosure of users' behavior privacy in online business activities has attracted people's wide attention. Aiming at the protection of users' commodity viewing privacy in a commercial website, this paper proposes to construct a group of dummy requests on a trusted client, then, which are submitted together with a user commodity viewing request to the untrusted server-side, so as to confuse and cover up the user preferences. First, we define a privacy model for a user commodity viewing service, in which we introduce a concept called entropy for commodity viewing probability to measure the confusion effect of dummy requests on user requests, and we introduce a concept called regional distance among commodity categories to measure the cover-up effect of dummy requests on users' commodity viewing preferences. Second, we design an implementation algorithm to generate a group of ideal dummy requests that can meet the constraints formulated in the privacy model. Finally, both theoretical analysis and experimental evaluation demonstrate the effectiveness of the proposed approach, i.e., which can improve the security of users' commodity viewing privacy on the untrusted server-side, without compromising the availability of an e-commerce website. In this paper, we present a valuable research attempt to the protection of users' behavior privacy in a commercial website, which is of positive significance for building a privacy-preserving e-commerce platform. (c) 2021 Elsevier B.V. All rights reserved.