[1] YU S,ZHOU W,GUO S,et al.A feasible IP traceback framework through dynamic deterministic packet marking[J].IEEE Transactions on Computers,2016,65(5):1418-1427.
[2] 杨高明,朱海明,方贤进,等.局部差分隐私约束的关联属性不变后随机响应扰动[J].电子学报,2019,47(5):105-111. Yang Gao-ming,Zhu Hai-ming,Fang Xie-jin,et al.Invariant post-random response perturbation for correlated attributes under local differential privacy constraint[J].Acta Electronica Sinica,2019,47(5):105-111.(in Chinese)
[3] 鲜征征,李启良,黄晓宇,等.融合显/隐式信任协同过滤算法的差分隐私保护[J].电子学报,2018,46(12):236-245. Xian Zheng-zheng,Li Qi-liang,Huang Xiao-yu,et al.Differential privacy protection for collaborative filtering algorithms with explicit and implicit trust[J].Acta Electronica Sinica,2018,46(12):236-245.(in Chinese)
[4] FU A M,YU S,ZHANG Y Q,et al.NPP:a new privacy-aware public auditing scheme for cloud data sharing with group users[J].IEEE Transactions on Big Data,DOI:10.1109/TBDATA.2017.2701347,2017.
[5] OGANIAN A,DOMINGO-FERRY J.Local synthesis for disclosure limitation that satisfies probabilistic k-anonymity criterion[J].Transactions on Data Privacy,2017,10(1):61-81.
[6] SORIA-COMAS J,DOMINGO-FERRER J,SANCHEZ D,et al.t-closeness through microaggregation:strict privacy with enhanced utility preservation[J].IEEE Transactions on Knowledge and Data Engineering,2015,27(11):3098-3110.
[7] DWORK C.Differential privacy[J].Lecture Notes in Computer Science,2006,26(2):1-12.
[8] YIN C,XI J,SUN R,et al.Location privacy protection based on differential privacy strategy for big data in industrial Internet of Things[J].IEEE Transactions on Industrial Informatics,2017,14(8):3628-3636.
[9] QU Y Y,YU S,GAO L X,et al.Big data set privacy preserving through sensitive attribute-based grouping[A].International Conference on Communications (ICC)[C].Paris,France:IEEE,2017.1-6.
[10] DRAKONAKIS K,ILIA P,IOANNIDIS S,et al.Please forget where I was last summer:the privacy risks of public location (meta) data[A].26th Annual Network and Distributed System Security Symposium (NDSS)[C].San Diego,USA:ISOC,2019.1-15.
[11] YE Q Q,HU H B,MENG X F,et al.PrivKV:key-value data collection with local differential privacy[A].Symposium on Security and Privacy (S&P)[C].San Francisco,USA:IEEE,2019.1-15.
[12] DUAN Y,YOUDAO N E,CANNY J,et al.P4P:practical large-scale privacy-preserving distributed computation robust against malicious users[A].19th USENIX Security Symposium (USENIX)[C].Washington,USA:ACM,2010.1-15.
[13] NI L,LI C,WANF X,et al.DP-MCDBSCAN:differential privacy preserving multi-core DBSCAN clustering for network user data[J].IEEE Access,2018,6:21053-21063.
[14] LV C,XING Y,ZHAN J,et al.Levenberg-marquardt backpropagation training of multilayer neural networks for state estimation of a safety critical cyber-physical system[J].IEEE Transactions on Industrial Informatics,2017,14(8):3436-3446.
[15] LICHMAN M.UCI Machine Learning Repository[EB/OL]:http://archive.ics.uci.edu/ml,2013.
[16] GREFF K,SRIVASTAVA R K,KOUTNIK J,et al.LSTM:a search space odyssey[J].IEEE Transactions on Neural Networks and Learning Systems,2016,28(10):2222-2232. |