面向SVM的隐私保护方法研究进展
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摘要
针对未来应用SVM进行数据挖掘所面临的信息安全问题,对隐私保护支持向量机分类规则挖掘方法进行研究,以提高支持向量机进行分类时的数据安全性,同时获得有效结果.分析了支持向量机分类方法的特点和可能面临的安全威胁;对国内外相关研究成果进行了归纳和梳理;重点从数据干扰和数据加密2个角度,给出了支持向量机隐私保护技术的最新研究进展;归纳出目前研究存在的问题和未来研究的趋势.指出了支持向量机隐私保护的研究方向:分布式环境下局部分类器融合隐私保护策略、更高效率的全同态加密方案、保护SVM分类规则的方案以及适用于大数据挖掘的隐私保护SVM技术.
To realize information security for future support vector machines(SVM) data mining,the privacy-preserving support vector machines(PPSVM) was investigated to obtain effective result.The characteristics of SVM classifiers were analyzed to find the security hole.The latest literatures and related research were summarized.The recent progress of privacy-preserving support vector machines was presented based on data perturbation and data encryption.The future hot research directions of new privacy-preserving support vector machine technologies in distributed environment,more effective fully homomorphic encryption(FHE) schemes and privacy-preserving support vector machine technologies for big data mining were pointed out.
To realize information security for future support vector machines(SVM) data mining,the privacy-preserving support vector machines(PPSVM) was investigated to obtain effective result.The characteristics of SVM classifiers were analyzed to find the security hole.The latest literatures and related research were summarized.The recent progress of privacy-preserving support vector machines was presented based on data perturbation and data encryption.The future hot research directions of new privacy-preserving support vector machine technologies in distributed environment,more effective fully homomorphic encryption(FHE) schemes and privacy-preserving support vector machine technologies for big data mining were pointed out.
引文
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[18]WANG T Y,WU C H.Detection of packed executables using support vector machines[C]∥Proceedings of2011 International Conference on Machine Learning and Cybernetics.Piscataway:IEEE Computer Society,2011:717-722.
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[26]ATAK F.Secure multi-party computation based privacy preserving extreme learning machine algorithm over vertically distributed data[C]∥Proceedings of the 22nd International Conference on Neural Information Processing.Heidelberg:Springer Verlag,2015:337-345.
[27]BRAKERSKI Z,GENTRY C,VAIKUNTANATHAN V.(Leveled)fully homomorphic encryption without bootstrapping[C]∥Proceedings of the 3rd Conference on Innovations in Theoretical Computer Science.New York:ACM,2012:309-325.
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[29]BRAKERSKI Z,VAIKUNTANATHAN V.Efficient fully homomorphic encryption from(standard)lwe[J].SIAM Journal on Computing,2014,43(2):831-871.
[30]PAILLIER P.Public-key cryptosystems based on composite degree residuosity classes[C]∥Proceedings of the 7th International Conference on the Theory and Application of Cryptographic Techniques.Heidelberg:Springer Verlag,1999:223-238.
[31]MESHRAM C,MESHRAM S A.An identity-based cryptographic model for discrete logarithm and integer factoring based cryptosystem[J].Information Processing Letters,2013,113(10/11):375-380.
[32]HU Y H,HE G P,FANG L,et al.Privacy-preserving SVM classification on arbitrarily partitioned data[C]∥Proceedings of the 2010 IEEE International Conference on Progress in Informatics and Computing.Piscataway:IEEE Computer Society,2010:67-71.
[33]GENTRY C.Fully homomorphic encryption using ideal lattices[C]∥Proceedings of the 2009 ACM International Symposium on Theory of Computing.New York:ACM,2009:169-178.
[34]TRONCOSO-PASTORIZA J R,GONZALEZ-JIMENEZ D,PEREZ-GONZALEZ F.Fully private noninteractive face verification[J].IEEE Transactions on Information Forensics and Security,2013,8(7):1101-1114.
[35]TAN W X,ZHAO C J,WU H R,et al.A homomorphic encryption scheme for agriculture cloud service based on vector operation[J].Journal of Computational Information Systems,2013,9(14):5735-5742.
[36]TEO S G,HAN S G,LEE V C S.Privacy preserving support vector machine using non-linear kernels on hadoop mahout[C]∥Proceedings of the 16th IEEE International Conference on Computational Science and Engineering.Piscataway:IEEE Computer Society,2013:941-948.
[37]GENTRY C,HALEVI S.Implementing Gentry's fullyhomomorphic encryption scheme[C]∥Proceedings of the 30th Annual International Conference on the Theory and Applications of Cryptographic Techniques Advances in Cryptology.Heidelberg:Springer Verlag,2011:129-148.
[38]OKKALIOGLU B D,OKKALIOGLU M,KOC M,et al.A survey:deriving private information from perturbed data[J].Artificial Intelligence Review,2015,44(4):547-569.
[39]LEE Y J,MANGASARIAN O L.RSVM:reduced support vector machines[C]∥Proceedings of the First SIAM International Conference on Data Mining.New York:ACM,2001:57-64.
[40]MANGASARIAN O L,WILD E W.Privacy-preserving classification of horizontally partitioned data via random kernels[C]∥Proceedings of the 2008 International Conference on Data Mining.Bogart,United States:CSREA Press,2008:473-479.
[41]MANGASARIAN O L,WILD E W,FUNG G M.Privacy-preserving classification of vertically partitioned data via random kernels[J].ACM Transactions on Knowledge Discovery from Data,2008,doi:10.1145/1409620.1409622.
[42]MANGASARIAN O L,WILD E W.Privacy-preserving random kernel classification of checkerboard partitioneddata[M]∥APTE U,KARMARKAR U.Managing in the Information Economy:Current Research Issues(Annals of Information Systems).New York:Springer Verlag,2010:375-387.
[43]SUN L,MU W S,QI B,et al.A new privacy-preserving proximal support vector machine for classification of vertically partitioned data[J].International Journal of Machine Learning and Cybernetics,2014,6(1):109-118.
[44]LIN K P,CHEN M S.Privacy-preserving outsourcing support vector machines with random transformation[C]∥Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.New York:ACM,2010:363-372.
[45]ALOTAIBI K,DE LA I B.Privacy-preserving SVM classification using non-metric MDS[C]∥Proceedings of the 7th International Conference on Emerging Security Information.United States:International Academy,Research and Industry Association,2013:30-35.
[46]胡文军,王士同.隐私保护的SVM快速分类方法[J].电子学报,2012,40(2):280-286.HU W J,WANG S T.Fast classification approach of support vector machine with privacy preservation[J].Acta Electronica Sinica,2012,40(2):280-286.(in Chinese)
[47]张战成,王士同,钟富礼.具有隐私保护功能的协作式分类机制[J].计算机研究与发展,2011,48(6):1018-1028.ZHANG Z C,WANG S T,CHUNG F L.Collaborative classification mechanism for privacy-preserving[J].Journal of Computer Research and Development,2011,48(6):1018-1028.(in Chinese)
[48]SUN X,LI L,WANG Z Q.Using manifold learning and minimax probability machine for face recognition[C]∥Proceedings of the 2010 2nd International Conference on Modeling,Simulation,and Visualization Methods.New York:ACM,2010:229-232.
[2]AGRAWAL R,SRIKANT R.Privacy-preserving data mining[C]∥Proceedings of the ACM SIGMOD International Conference on Management of Data.Piscataway:IEEE,2000:439-450.
[3]FUNG B C M,WANG K,CHEN R,et al.Privacy-preserving data publishing:a survey of recent developments[J].ACM Computing Surveys,2010,doi:10.1145/1749603.1749605.
[4]WU X D,ZHU X Q,WU G Q,et al.Data mining with big data[J].IEEE Transactions on Knowledge and Data Engineering,2014,26(1):97-107.
[5]YU H,VAIDYA J,JIANG X Q.Privacy-preserving SVM classification on vertically partitioned data[C]∥Proceedings of the 10th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining.Heidelberg:Springer Verlag,2006:647-656.
[6]YU H,JIANG X Q,VAIDYA J.Privacy-preserving SVM using nonlinear kernels on horizontally partitioned data[C]∥Proceedings of the 2006 ACM Symposium on Applied Computing.New York:ACM,2006:603-610.
[7]LU Y M,PHOUNGPHOL P,ZHANG Y Q.Privacy aware non-linear support vector machine for multi-source big data[C]∥Proceedings of the 2014 IEEE 13th International Conference on Trust,Security and Privacy in Computing and Communications.Piscataway,USA:IEEE,2015:783-789.
[8]VAIDYA J,YU H,JIANG X Q.Privacy-preserving SVM classification[J].Knowledge and Information Systems,2008,14(2):161-178.
[9]LEVER A.On Privacy[M].London:Routledge,2011.
[10]沈中,许文洁.隐私权论兼析人格权[M].上海:上海人民出版社,2010.
[11]ARNOLD M,ADAMSON G.A critique of privacy[C]∥Proceedings of the 2010 IEEE International Symposium on Technology and Society.Piscataway:IEEE,2010:427-434.
[12]CHOI B C F,JIANG Z H,RAMESH B,et al.Privacy tradeoff and social application usage[C]∥Proceedings of the 48th Annual Hawaii International Conference on System Sciences.Piscataway:IEEE Computer Society,2015:304-313.
[13]WANG P S.Survey on privacy preserving data mining[J].International Journal of Digital Content Technology and Its Applications,2010,4(9):1-7.
[14]德勤企业风险管理服务部.个人信息保护—应对法律合规要求,妥善处理个人信息[M].上海:上海交通大学出版社,2013.
[15]朱庆华,颜祥林,袁勤俭.信息法教程[M].2版.北京:高等教育出版社,2011.
[16]CHEN T S,CHEN J,LIN Y C,et al.A novel knowledge protection technique base on support vector machine model for anti-classification[J].Lecture Notes in Electrical Engineering,2011,98:517-524.
[17]RAHULAMATHAVAN Y,VELURU S,PHAN R C W,et al.Privacy-preserving clinical decision support system using Gaussian kernel-based classification[J].IEEE Journal of Biomedical and Health Informatics,2014,18(1):56-66.
[18]WANG T Y,WU C H.Detection of packed executables using support vector machines[C]∥Proceedings of2011 International Conference on Machine Learning and Cybernetics.Piscataway:IEEE Computer Society,2011:717-722.
[19]祁正华,杨庚,任勋益,等.标准模型下基于身份的多接收者签密方案[J].江苏大学学报(自然科学版),2011,32(5):573-577.QI Z H,YANG G,Ren X Y,et al.An ID-based signcryption scheme for multiple receivers in standard model[J].Journal of Jiangsu University(Natural Science Edition),2011,32(5):573-577.(in Chinese)
[20]TIAN T,DUAN H,HE G P.Privacy-preserving classification on horizontally partitioned data[C]∥Proceedings of the 2010 International Conference on Computational Intelligence and Security.Piscataway:IEEE Computer Society,2010:230-233.
[21]LIN K P,CHEN M S.Releasing the SVM classifier with privacy-preservation[C]∥Proceedings of the 8th IEEE International Conference on Data Mining.Piscataway:IEEE,2008:899-904.
[22]LIN K P,CHEN M S.On the design and analysis of theprivacy-preserving SVM classifier[J].IEEE Transactions on Knowledge and Data Engineering,2011,23(11):1704-1717.
[23]刘忠宝,王士同.面向大规模数据的隐私保护学习机[J].电子科技大学学报,2013,42(2):272-277.LIU Z B,WANG S T.Privacy preserving learning machine for large scale datasets[J].Journal of University of Electronic Science and Technology of China,2013,42(2):272-277.(in Chinese)
[24]YAO A C.Protocols for secure computations[C]∥Proceedings of the 23rd Annual Symposium on Foundations of Computer Science.New York:IEEE,1982:160-164.
[25]王良民,茅冬梅,梁军.基于RFID系统的隐私保护技术[J].江苏大学学报(自然科学版),2012,33(6):690-695,744.WANG L M,MAO D M,LIANG J.Privacy protection technology for RFID system[J].Journal of Jiangsu University(Natural Science Edition),2012,33(6):690-695,744.(in Chinese)
[26]ATAK F.Secure multi-party computation based privacy preserving extreme learning machine algorithm over vertically distributed data[C]∥Proceedings of the 22nd International Conference on Neural Information Processing.Heidelberg:Springer Verlag,2015:337-345.
[27]BRAKERSKI Z,GENTRY C,VAIKUNTANATHAN V.(Leveled)fully homomorphic encryption without bootstrapping[C]∥Proceedings of the 3rd Conference on Innovations in Theoretical Computer Science.New York:ACM,2012:309-325.
[28]VAN D M,GENTRY C,HALEVI S,et al.Fully homomorphic encryption over the integers[C]∥Proceedings of the 29th Annual International Conference on the Theory and Applications of Cryptographic Techniques.Heidelberg:Springer Verlag,2010:24-43.
[29]BRAKERSKI Z,VAIKUNTANATHAN V.Efficient fully homomorphic encryption from(standard)lwe[J].SIAM Journal on Computing,2014,43(2):831-871.
[30]PAILLIER P.Public-key cryptosystems based on composite degree residuosity classes[C]∥Proceedings of the 7th International Conference on the Theory and Application of Cryptographic Techniques.Heidelberg:Springer Verlag,1999:223-238.
[31]MESHRAM C,MESHRAM S A.An identity-based cryptographic model for discrete logarithm and integer factoring based cryptosystem[J].Information Processing Letters,2013,113(10/11):375-380.
[32]HU Y H,HE G P,FANG L,et al.Privacy-preserving SVM classification on arbitrarily partitioned data[C]∥Proceedings of the 2010 IEEE International Conference on Progress in Informatics and Computing.Piscataway:IEEE Computer Society,2010:67-71.
[33]GENTRY C.Fully homomorphic encryption using ideal lattices[C]∥Proceedings of the 2009 ACM International Symposium on Theory of Computing.New York:ACM,2009:169-178.
[34]TRONCOSO-PASTORIZA J R,GONZALEZ-JIMENEZ D,PEREZ-GONZALEZ F.Fully private noninteractive face verification[J].IEEE Transactions on Information Forensics and Security,2013,8(7):1101-1114.
[35]TAN W X,ZHAO C J,WU H R,et al.A homomorphic encryption scheme for agriculture cloud service based on vector operation[J].Journal of Computational Information Systems,2013,9(14):5735-5742.
[36]TEO S G,HAN S G,LEE V C S.Privacy preserving support vector machine using non-linear kernels on hadoop mahout[C]∥Proceedings of the 16th IEEE International Conference on Computational Science and Engineering.Piscataway:IEEE Computer Society,2013:941-948.
[37]GENTRY C,HALEVI S.Implementing Gentry's fullyhomomorphic encryption scheme[C]∥Proceedings of the 30th Annual International Conference on the Theory and Applications of Cryptographic Techniques Advances in Cryptology.Heidelberg:Springer Verlag,2011:129-148.
[38]OKKALIOGLU B D,OKKALIOGLU M,KOC M,et al.A survey:deriving private information from perturbed data[J].Artificial Intelligence Review,2015,44(4):547-569.
[39]LEE Y J,MANGASARIAN O L.RSVM:reduced support vector machines[C]∥Proceedings of the First SIAM International Conference on Data Mining.New York:ACM,2001:57-64.
[40]MANGASARIAN O L,WILD E W.Privacy-preserving classification of horizontally partitioned data via random kernels[C]∥Proceedings of the 2008 International Conference on Data Mining.Bogart,United States:CSREA Press,2008:473-479.
[41]MANGASARIAN O L,WILD E W,FUNG G M.Privacy-preserving classification of vertically partitioned data via random kernels[J].ACM Transactions on Knowledge Discovery from Data,2008,doi:10.1145/1409620.1409622.
[42]MANGASARIAN O L,WILD E W.Privacy-preserving random kernel classification of checkerboard partitioneddata[M]∥APTE U,KARMARKAR U.Managing in the Information Economy:Current Research Issues(Annals of Information Systems).New York:Springer Verlag,2010:375-387.
[43]SUN L,MU W S,QI B,et al.A new privacy-preserving proximal support vector machine for classification of vertically partitioned data[J].International Journal of Machine Learning and Cybernetics,2014,6(1):109-118.
[44]LIN K P,CHEN M S.Privacy-preserving outsourcing support vector machines with random transformation[C]∥Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.New York:ACM,2010:363-372.
[45]ALOTAIBI K,DE LA I B.Privacy-preserving SVM classification using non-metric MDS[C]∥Proceedings of the 7th International Conference on Emerging Security Information.United States:International Academy,Research and Industry Association,2013:30-35.
[46]胡文军,王士同.隐私保护的SVM快速分类方法[J].电子学报,2012,40(2):280-286.HU W J,WANG S T.Fast classification approach of support vector machine with privacy preservation[J].Acta Electronica Sinica,2012,40(2):280-286.(in Chinese)
[47]张战成,王士同,钟富礼.具有隐私保护功能的协作式分类机制[J].计算机研究与发展,2011,48(6):1018-1028.ZHANG Z C,WANG S T,CHUNG F L.Collaborative classification mechanism for privacy-preserving[J].Journal of Computer Research and Development,2011,48(6):1018-1028.(in Chinese)
[48]SUN X,LI L,WANG Z Q.Using manifold learning and minimax probability machine for face recognition[C]∥Proceedings of the 2010 2nd International Conference on Modeling,Simulation,and Visualization Methods.New York:ACM,2010:229-232.