计算机科学 ›› 2017, Vol. 44 ›› Issue (5): 81-88.doi: 10.11896/j.issn.1002-137X.2017.05.015
鲜征征,李启良,李改,李磊
XIAN Zheng-zheng, LI Qi-liang, LI Gai and LI Lei
摘要： 利用背景知识间接推导出个人隐私信息已成为Internet用户更担忧的问题,定义极为严格且可证明的差分隐私保护是目前解决该问题的最有效的隐私保护技术。Berlioz等将差分隐私保护技术应用于协同过滤算法之一的矩阵分解中,虽然提出了新的算法,但是缺少严格的证明过程。针对他们提出的算法,将补充相应的数学证明,然后 将Chaudhuri等提出的目标函数加扰方法灵活应用于ALS目标函数中。此外,还给出一种差分隐私保护参数的选择方案。最后,在两个真实数据集上的实验验证结果表明,所提出的ALS目标函数加扰方法取得了更好的推荐效果。
| [1] BERLIOZ A,FRIEDMAN A,KAAFAR M A,et al.Applying Differential Privacy to Matrix Factorization[C]∥Proceedings of the 9th ACM Conference on Recommender Systems.Vienna,Austria,2015:107-114. [2] DWORK C.Differential Privacy[C]∥33rd International Colloquium on Automata,Languages and Programming,part II (ICALP 2006).Italy,2006:1-12. [3] CHAUDHURI K,MONTELEONI C,SARWATE A.Differentially private empirical risk minimization[J].Journal of Machine Learning Research,2011,2:1069-1109. [4] DESROSIERS C,KARYPIS G.A comprehensive survey of nei-ghborhood-based recommeddation methods[M]∥Rec.Sys.Handbook.2001:107-144. [5] CANNY J.Collabrative filting with privacy[J].IEEE Security and Privacy,2002,18(1):45-57. [6] POLAT H,DU W.Achieving private recommendations usingrandomized response techniques[C]∥PAKDD.2006:637-646. [7] NIKOLAENKO V,IOANNIDIS S,WEINSBERG U,et al.Privacy-preserving matrix factorization[C]∥CCS.2013:801-812. [8] CALANDRINO J A,KILZER A,NARAYANAN A,et al.“youmight also like:”privacy risks of collaborative filtering[C]∥IEEE Security and Privacy.2011:231-246. [9] CHEN R,MOHAMMED N,FUNG B C M,et al.Publishing Set-Valued Data via Differential Privacy[C]∥Proceedings of the 37nd Conference of Very Large Databases (VLDB).Seattle,Washington,USA,2011:1087-1098. [10] CHEN R,FUNG B C M,et al.Differentially Private Transit Data Publication:A Case Study on the Montreal Transportation System[C]∥Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD).Beijing,China,2012:493-502. [11] FRIEDMAN A,SCHUSTER A.Data Mining with Differential Privacy[C]∥Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD).Washington,DC,USA,2010:493-502. [12] MACHANAVAJJHALA A,KOROLOVA A,SARMA A D.Personalized social recommendations-arrcurate or private[J].PVLDB,2011,4(7):440-450. [13] MCSHERRY F,MIRONOV I.Differential Private recommender System:Building privacy into Netflix prize conteders[C]∥KDD.Paris,France,2009:627-636. [14] LIU Z Q,WANG Y X,SMOLA,et al.Fast Differentially Private Matrix Factorization[C]∥Proceedings of the 9th ACM Confe-rence on Recommender Systems.Vienna,Austria,2015:171-178. [15] HUA J Y,XIA C,ZHONG S.Differentially private matrix factorization[C]∥Proceedings of the 24th International Conference on Artificial Intelligence.Buenos Aires,Argentina,2015:1763-1770. [16] SWEENEY L.K-anonymity:A model of for protecting privacy[J].International Journal of Uncertainty,Fuzziness and Know-ledge Based System,2002,10(5):557-570. [17] LI Y,ZHANG X Z.Survey of Research on Differential Privacy[J].Journal of Application Research of Computers,2012,9(9):3201-3211.(in Chinese) 李杨,张新政.差分隐私保护综述[J].计算机应用研究,2012,9(9):3201-3211. [18] ZHANG X J,MENG X F.A Survey of Differential Privacy in Data Publication and Analysis[J].Chinese Journal of Compu-ters,2014,7(4):929-949.(in Chinese) 张啸剑,孟小峰.面向数据发布和分析的差分隐私保护研究[J].计算机学报,2014,7(4):929-949. [19] DWORK C.Differential Privacy:A Survey of Results[C]∥Theo-ry and Applications of Models of Computation(TAMC2008).Berlin,2008:1-9. [20] NISSIM K,RASKHODNIKOVA S,SMITH A.Smooth sensitivity and sampling in private data analysis[C]∥Proceedings of the 39th Annual ACM Symposium on Theroy of Computing.San Diego,USA,2007:75-84. [21] DWORK C,MCSHERRY F,NISSIMK,et al.Calibrating Noise to Sensitivity in Private Data Analysis[C]∥Proceedings of the 3th Theory of Cryptography Conference (TCC).New York,USA,2006:363-385. [22] MCSHERRY F.Privacy Integrated Queries:An Extensible Plat-form for Privacy-Preserving Data Analysis[C]∥Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD).Providence,Rhode Island,USA,2009:19-30. |
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