Method of privacy protection based on multiple edge servers in personalized search

被引：0
|
作者：
Zhang Q. [1 ]
Wang G. [2 ]
Zhang S. [3 ]
机构：
[1] School of Information Science and Engineering, Central South University, Changsha
[2] School of Computer Science and Cyber Engineering, Guangzhou University, Guangzhou
[3] School of Computer Science and Engineering, Hunan University of Science and Technology, Xiangtan
来源：
Tongxin Xuebao/Journal on Communications | 2019年 / 40卷 / 02期
基金：
中国国家自然科学基金;
关键词：
Edge server; Index cutting; Personalized search; Privacy protection; Searchable encryption;
D O I：
10.11959/j.issn.1000-436x.2019024
中图分类号：
学科分类号：
摘要：
In the plaintext environment, users' personalized search results can be obtained through users' interest model and query keywords. However, it may possibly result in the disclosure of sensitive data and privacy, which prevents using sensitive data in cloud search. Therefore, data is generally stored in the form of ciphertext in the cloud server. In the process of cloud search service, users intend to quickly obtain the desired search results from the vast amount of ciphertext. In order to solve the problem, it was proposed that a method of privacy protection based on multiple edge servers in personalized search shall be used. By introducing multiple edge servers and cutting the index as well as the query matrix, the computing relevance scores of partial query and partial file index are achieved on the edge server. The cloud server only needs to get the relevance score on the edge server and make a simple processing that can return to the most relevant Top K files by user query, so as to make it particularly suitable for a large number of users in the massive personalized ciphertext search. Security analysis and experimental results show that this method can effectively protect users' privacy and data confidentiality. In addition, it can guarantee high efficiency in search to provide better personalized search experience. © 2019, Editorial Board of Journal on Communications. All right reserved.
引用
收藏
页码：40 / 50
页数：10
相关论文
共 26 条
  • [1] Tang J., Cui Y., Li Q., Et al., Ensuring security and privacy preservation for cloud data services, Acm Computing Surveys, 49, 1, pp. 1-39, (2016)
  • [2] Song D.X., Wagner D., Perrig A., Practical techniques for searches on encrypted data, IEEE Symposium on Security & Privacy, pp. 44-55, (2002)
  • [3] Li H.W., Liu D.X., Dai Y.S., Et al., Engineering searchable encryption of mobile cloud networks: when QoE meets QoP, IEEE Wireless Communications, 22, 4, pp. 74-80, (2015)
  • [4] Chang Y.C., Mitzenmacher M., Privacy preserving keyword searches on remote encrypted data, International Conference on Applied Cryptography and Network Security, pp. 442-455, (2005)
  • [5] Curtmola R., Garay J., Kamara S., Et al., Searchable symmetric encryption: improved definitions and efficient constructions, Journal of Computer Security, 19, 5, pp. 895-934, (2011)
  • [6] Dan B., Crescenzo G.D., Ostrovsky R., Et al., Public key encryption with keyword search, International Conference on the Theory and Applications of Cryptographic Techniques, pp. 506-522, (2004)
  • [7] Li J.W., Jia C.F., Liu Z.L., Et al., Survey on the searchable encryption, Journal of Software, 26, 1, pp. 109-128, (2015)
  • [8] Cui J., Zhou H., Zhong H., Et al., AKSER: attribute-based keyword search with efficient revocation in cloud computing, Information Sciences, 423, pp. 343-352, (2017)
  • [9] Zhao F., Yan F.W., Jin H., Et al., Personalized mobile searching approach based on combining content-based filtering and collaborative filtering, IEEE Systems Journal, 11, 1, pp. 324-332, (2017)
  • [10] Leung W.T., Lee D.L., Lee W.C., PMSE: a personalized mobile search engine, IEEE Transactions on Knowledge & Data Engineering, 25, 4, pp. 820-834, (2013)
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