鲜英,于炯,杨兴耀,薛朋强

• 1:新疆大学信息科学与工程学院
• 2:新疆大学研究生院
• 3:新疆大学软件学院

摘要(Abstract)：

现有的k-匿名隐私保护是一种安全有效的隐私保护算法,针对其对背景知识攻击和同质性攻击防范的不足,提出一种基于敏感属性多样性的微聚集隐私保护的协同过滤算法。算法在满足k-匿名的前提下,融入敏感属性的多样性,在微聚集算法中通过设置同一等价类中敏感属性的差异值,来避免敏感属性值过于接近而造成隐私泄露,从而达到保护隐私数据的目的,同时保证推荐的准确性。实验结果表明,该算法既能保证为用户提供高效的个性化推荐,又能够产生安全的信息表。

关键词(KeyWords)： 推荐系统;微聚集;协同过滤;k-匿名化;隐私泄露;隐私保护

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金项目(61462079);国家自然科学基金项目(61262088);国家自然科学基金项目(61562086);国家自然科学基金项目(61363083)~~

作者(Author): 鲜英,于炯,杨兴耀,薛朋强

DOI: 10.16652/j.issn.1004-373x.2018.06.002

参考文献(References)：

• [1]夏赞珠.微数据发布中的隐私保护匿名化算法研究[D].金华:浙江师范大学,2011.XIA Zanzhu.Research on microdata anonymity algorithms for privacy-preservation data publishing[D].Jinhua:Zhejiang Normal University,2011.
• [2]CASINO F,DOMINGO-FERRER J,PATSAKIS C,et al.A k-anonymous approach to privacy preserving collaborative filtering[J].Journal of computer&system sciences,2015,81(6):1000-1011.
• [3]CASINO F,DOMINGO-FERRER J,PATSAKIS C,et al.Privacy preserving collaborative filtering with k-anonymity through microaggregation[C]//Proceedings of the 2013 IEEE 10th International Conference on E-Business Engineering.Washington:IEEE Computer Society,2013:490-497.
• [4]ZHU T,REN Y,ZHOU W,et al.An effective privacy preserving algorithm for neighborhood-based collaborative filtering[J].Future generation computer systems,2014,36(36):142-155.
• [5]TANG Q,WANG J.Privacy-preserving context-aware recommender systems:analysis and new solutions[C]//Proceedings of European Symposium on Research in Computer Security.Berlin:Springer,2015:101-119.
• [6]夏建勋,吴非,谢长生.应用数据填充缓解稀疏问题实现个性化推荐[J].计算机工程与科学,2013,35(5):15-19.XIA Jianxun,WU Fei,XIE Changsheng.Applying data filling to alleviate the sparsity problem for personalized recommendation[J].Computer engineering and science,2013,35(5):15-19.
• [7]杨兴耀,于炯,吐尔根·依布拉音,等.融合奇异性和扩散过程的协同过滤模型[J].软件学报,2013,24(8):1868-1884.YANG Xingyao,YU Jiong,IBRAHIM Turgun,et al.Collaborative filtering model fusing singularity and diffusion process[J].Journal of software,2013,24(8):1868-1884.
• [8]LIU B,HENGARTNER U.Privacy-preserving social recommendations in geosocial networks[C]//Proceedings of 2013Eleventh Annual International Conference on Privacy,Security and Trust.Tarragona:IEEE,2013:69-76.
• [9]CLEMENTE F J G.A privacy-preserving recommender system for mobile commerce[C]//Proceedings of 2015 IEEE Conference on Communications and Network Security.Florence:IEEE,2015:725-726.
• [10]周长利,马春光,杨松涛.路网环境下保护LBS位置隐私的连续KNN查询方法[J].计算机研究与发展,2015,52(11):2628-2644.ZHOU Changli,MA Chunguang,YANG Songtao.Location privacy-preserving method for LBS continuous KNN query in road networks[J].Journal of computer research and development,2015,52(11):2628-2644.
• [11]王国霞,王丽君,刘贺平.个性化推荐系统隐私保护策略研究进展[J].计算机应用研究,2012,29(6):2001-2008.WANG Guoxia,WANG Lijun,LIU Heping.Study progress of privacy protection techniques used in personalized recommendation system[J].Application research of computers,2012,29(6):2001-2008.
• [12]张小波,付达杰.网络信息资源个性化推荐中隐私保护的研究[J].软件,2015,36(4):62-66.ZHANG Xiaobo,FU Dajie.Research on privacy protection in the personalized recommendation of network information resources[J].Software,2015,36(4):62-66.
• [13]孙广中,魏燊,谢幸.大数据时代中的去匿名化技术及应用[J].信息通信技术,2013,7(6):52-57.SUN Guangzhong,WEI Shen,XIE Xing.De-anonymization technology and applications in the age of big data[J].Information and communications technologies,2013,7(6):52-57.
• [14]张学军,桂小林,伍忠东.位置服务隐私保护研究综述[J].软件学报,2015,26(9):2373-2395.ZHANG Xuejun,GUI Xiaolin,WU Zhongdong.Privacy preservation for location-based services:a survey[J].Journal of software,2015,26(9):2373-2395.
• [15]叶阿勇,李亚成,马建峰,等.基于服务相似性的k-匿名位置隐私保护方法[J].通信学报,2014,35(11):162-169.YE Ayong,LI Yacheng,MA Jianfeng,et al.Location privacypreserving method of k-anonymous based-on service similarity[J].Journal on communications,2014,35(11):162-169.