基于用户项目特征分组的隐私保护算法
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摘要
针对互联网推荐系统中存在严重的隐私保护问题,在传统推荐系统算法的基础上,引入项目属性相似度的概念,并提出了一种具备保护用户隐私功能的新型推荐系统.系统利用用户的历史评价和推荐系统中项目的属性信息,使用不采集用户个人信息的协同过滤推荐算法,计算出用户对未评价项目的评分预测,形成了一种能够保护个人隐私的推荐算法.结果表明,与其他推荐算法相比,本文算法在推荐准确度和用户隐私保护程度上取得一个较好的平衡,具有较高的实用价值.
Aiming at the serious privacy protection problem in the recommendation system of internet,the concept of project attribute similarity based on the traditional algorithm of recommender system was introduced,and a newrecommendation system with the function of protecting the privacy of users was proposed. With the historical evaluation of users and the attribute information of projects in the recommendation system,the collaborative filtering algorithm without collecting the personal information of users was adopted in the proposed system,the score forecast of projects without the evaluation of users could be calculated,and the recommendation algorithm which could protect the personal privacy was developed. The results showthat compared with other recommendation algorithms, the proposed recommendation algorithm achieves better balance between the recommendation accuracy and privacy protection degree of users,and has good practical value.
Aiming at the serious privacy protection problem in the recommendation system of internet,the concept of project attribute similarity based on the traditional algorithm of recommender system was introduced,and a newrecommendation system with the function of protecting the privacy of users was proposed. With the historical evaluation of users and the attribute information of projects in the recommendation system,the collaborative filtering algorithm without collecting the personal information of users was adopted in the proposed system,the score forecast of projects without the evaluation of users could be calculated,and the recommendation algorithm which could protect the personal privacy was developed. The results showthat compared with other recommendation algorithms, the proposed recommendation algorithm achieves better balance between the recommendation accuracy and privacy protection degree of users,and has good practical value.
引文
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[13]叶青,谷利泽,郑世慧,等.基于并发签名的网络易货协议[J].沈阳工业大学学报,2013,35(3):333-337.(YE Qing,GU Li-ze,ZHENG Shi-hui,et al. The netw ork barter agreement based on concurrent signature[J]. Journal of Shenyang University of Technology,2013,35(3):333-337.)
[14]严冬梅,鲁城华.基于用户兴趣度和特征的优化协同过滤推荐[J].计算机应用研究,2012,29(2):497-500.(YAN Dong-mei,LU Cheng-hua. Collaborative filtering recommendation based on optimization of user interest and characteristics[J]. Application Research of Computers,2012,29(2):497-500.)
[15]贾俊杰,闫国蕾.一种个性化(p,k)匿名隐私保护算法[J].计算机工程,2018(1):176-181.(JIA Jun-jie,YAN Guo-lei. A personalized(p,k)anonymous privacy protection algorithm[J]. Computer Engineering,2018(1):176-181.)
[16]毕猛,王安迪,徐剑,等.基于离散马尔科夫链的数据库用户异常行为检测[J].沈阳工业大学学报,2018,40(1):70-76.(BI Meng,WANG An-di,XU Jian,et al. Detection of abnormal behavior of database users based on discrete M arkov chain[J]. Journal of Shenyang University of Technology,2018,40(1):70-76.)
[2]蒲巧林.基于用户位置隐私保护的室内WLAN指纹定位组网优化算法[D].重庆:重庆邮电大学,2016.(PU Qiao-lin. Network optimization algorithm for indoor WLAN fingerprint location based on user location privacy protection[D]. Chongqing:Chongqing University of Posts and Telecommunications,2016.)
[3]智淑敏,刘静静.一种用于网络位置隐私保护的动态路由算法[J].电子设计工程,2016,24(15):28-31.(ZHI Shu-min,LIU Jing-jing. A dynamic routing algorithm for netw ork location privacy protection[J].Electronic Design Engineering,2016,24(15):28-31.)
[4]彭飞,曾学文,邓浩江,等.一种基于群组推荐的用户隐私保护方法[J].计算机应用研究,2015,32(3):869-872.(PENG Fei,ZENG Xue-wen,DENG Hao-jiang,et al.A user privacy protection method based on group recommendation[J]. Computer Application Research,2015,32(3):869-872.)
[5]孟凡帅.基于HDFS的时空数据共享与查询隐私保护的研究与实现[D].沈阳:东北大学,2014.(MENG Fan-shuai. Research and implementation of HDFS based spatio-temporal data sharing and query privacy protection[D]. Shenyang:Northeastern University,2014.)
[6]田文利.基于网络编码的节点隐私保护协议研究[J].电子设计工程,2015,23(3):49-50.(TIAN Wen-li. Privacy protection protocol of network based on node encoding[J]. Electronic Design Engineering,2015,23(3):49-50.)
[7]曹蔚,冯钢,秦爽,等.面向海量机器类通信(mMTC)的无线接入控制[J].重庆邮电大学学报(自然科学版),2017,29(5):569-579.(CAO Wei,FENG Gang,QIN Shuang,et al. Access control for massive machine type communications(mMTC)[J]. Journal of Chongqing University of Posts and Telecommunications(Natural Science Edition),2017,29(5):569-579.)
[8]程舒通,徐从富,但红卫.高效隐私保护频繁模式挖掘算法研究[J].计算机科学,2015,42(4):194-198.(CHENG Shu-tong,XU Cong-fu,DAN Hong-wei.Efficient privacy preserving frequent pattern mining algorithm[J]. Computer Science,2015,42(4):194-198.)
[9]张诗梦.集值数据发布中多级敏感模型及隐私保护方法研究[D].桂林:广西师范大学,2015.(ZHANG Shi-meng. Research on multilevel sensitive model and privacy protection in set-valued data publishing[D]. Guilin:Guangxi Normal University,2015.)
[10]王旭.汉语学习平台中基于BIRCH聚类的用户个人信息分组算法研究[D].长春:吉林大学,2011.(WANG Xu. Research on user personal information grouping algorithm based on BIRCH clustering in Chinese learning platform[D]. Changchun:Jilin University,2011.)
[11]陈超群.基于透明加密的移动终端数据防泄漏关键技术研究及应用[D].无锡:江南大学,2016.(CHEN Chao-qun. Research and application of key technology for anti leakage of mobile terminal based on transparent encryption[D]. Wuxi:Jiangnan University,2016.)
[12]康海燕,黄渝轩,陈楚翘.基于视频分析的地理信息隐私保护方法[J].山东大学学报(理学版),2018,53(1):19-29.(KANG Hai-yan,HUANG Yu-xuan,CHEN Chuqiao. The method of privacy protection of geographic information based on video analysis[J]. Journal of Shandong University(Science Edition),2018,53(1):19-29.)
[13]叶青,谷利泽,郑世慧,等.基于并发签名的网络易货协议[J].沈阳工业大学学报,2013,35(3):333-337.(YE Qing,GU Li-ze,ZHENG Shi-hui,et al. The netw ork barter agreement based on concurrent signature[J]. Journal of Shenyang University of Technology,2013,35(3):333-337.)
[14]严冬梅,鲁城华.基于用户兴趣度和特征的优化协同过滤推荐[J].计算机应用研究,2012,29(2):497-500.(YAN Dong-mei,LU Cheng-hua. Collaborative filtering recommendation based on optimization of user interest and characteristics[J]. Application Research of Computers,2012,29(2):497-500.)
[15]贾俊杰,闫国蕾.一种个性化(p,k)匿名隐私保护算法[J].计算机工程,2018(1):176-181.(JIA Jun-jie,YAN Guo-lei. A personalized(p,k)anonymous privacy protection algorithm[J]. Computer Engineering,2018(1):176-181.)
[16]毕猛,王安迪,徐剑,等.基于离散马尔科夫链的数据库用户异常行为检测[J].沈阳工业大学学报,2018,40(1):70-76.(BI Meng,WANG An-di,XU Jian,et al. Detection of abnormal behavior of database users based on discrete M arkov chain[J]. Journal of Shenyang University of Technology,2018,40(1):70-76.)