Computer Science ›› 2019, Vol. 46 ›› Issue (9): 99-105.doi: 10.11896/j.issn.1002-137X.2019.09.013
• NDBC 2018 • Previous Articles Next Articles
WU Ying-jie, HUANG Xin, GE Chen, SUN Lan
CLC Number:
[1]FUNG B C M,WANG K,CHEN R,et al.Privacy-preserving data publishing:A survey of recent developments[J].Acm Computing Surveys,2010,42(4):14. [2]DWORK C.Differential Privacy:A Survey of Results[C]//International Conference on Theory and Applications of MODELS of Computation.Springer-Verlag,2008:1-19. [3]ZHANG X J,MENG X F.Differential privacy in data publication and analysis[J].Chinese Journal of Computers,2014,37(4):927-949.(in Chinese)张啸剑,孟小峰.面向数据发布和分析的差分隐私保护[J].计算机学报,2014,37(4):927-949. [4]DWORK C,NAOR M,PITASSI T,et al.Differential privacyunder continual observation///Proc. of the 42nd ACM Symposium on Theory of Computing(STOC).New York:ACM,2010:715-724. [5]CHAN T H,SHI E,SONG D.Private and Continual Release of Statistics[J].ACM Trans. on Information and System Security,2011,14(3):1-24. [6]GE C,WU Y J,SUN L.A Real-time Publishing Method of Differential Privacy Streaming Data[OL].http://kns.cnki.net/kcms/detail/11.5602.TP.20171016.1629.004.html.(in Chinese)葛晨,吴英杰,孙岚.一种差分隐私流数据实时发布方法[OL].http://kns.cnki.net/kcms/detail/11.5602.TP.20171016.1629.004.html. [7]ZHANG X J,MENG X F.Stream histogram publication methodwith differential privacy[J].Journal of Software,2016,27(2):381-393.(in Chinese)张啸剑,孟小峰.基于差分隐私的流式直方图发布方法[J].软件学报,2016,27(2):381-393. [8]BOLOT J,FAWAZ N,MUTHUKRISHNAN S,et al.Privatedecayed predicate sums on streams[C]//Proceedings of the 16th International Conference on Extending Database Technology.New York:ACM,2013:284-295. [9]CHEN Y,MACHANAVAJJHALA A,HAY M,et al.PeGa-Sus:Data-Adaptive Differentially Private Stream Processing[C]//ACM Sigsac Conference.ACM,2017:1375-1388. [10]DWORK C,MCSHERRY F,NISSIM K,et al.Calibrating Noise to Sensitivity in Private Data Analysis[J].Lecture Notes in Computer Science,2012,3876(8):265-284. [11]FENWICK P M.A new data structure for cumulative frequency tables[J].Software Practice & Experience,1994,24(3):327-336. [12]LI C,HAY M,RASTOGI V,et al.Optimizing linear countingqueries under differential privacy[C]//Twenty-Ninth ACM Sigmod-Sigact-Sigart Symposium on Principles of Database Systems(PODS 2010).Indianapolis,Indiana,USA,DBLP,2010:123-134. [13]HAY M,RASTOGI V,MIKLAU G,et al.Boosting the accuracy of differentially private histograms through consistency[J].Proceedings of the Vldb Endowment,2010,3(1-2):1021-1032. [14]KELLARIS G,PAPADOPOULOS S,XIAO X,et al.Differen-tially private event sequences over infinite streams[J].Procee-dings of the Vldb Endowment,2014,7(12):1155-1166. |
[1] | TANG Ling-tao, WANG Di, ZHANG Lu-fei, LIU Sheng-yun. Federated Learning Scheme Based on Secure Multi-party Computation and Differential Privacy [J]. Computer Science, 2022, 49(9): 297-305. |
[2] | HUANG Jue, ZHOU Chun-lai. Frequency Feature Extraction Based on Localized Differential Privacy [J]. Computer Science, 2022, 49(7): 350-356. |
[3] | WANG Mei-shan, YAO Lan, GAO Fu-xiang, XU Jun-can. Study on Differential Privacy Protection for Medical Set-Valued Data [J]. Computer Science, 2022, 49(4): 362-368. |
[4] | KONG Yu-ting, TAN Fu-xiang, ZHAO Xin, ZHANG Zheng-hang, BAI Lu, QIAN Yu-rong. Review of K-means Algorithm Optimization Based on Differential Privacy [J]. Computer Science, 2022, 49(2): 162-173. |
[5] | DONG Xiao-mei, WANG Rui, ZOU Xin-kai. Survey on Privacy Protection Solutions for Recommended Applications [J]. Computer Science, 2021, 48(9): 21-35. |
[6] | SUN Lin, PING Guo-lou, YE Xiao-jun. Correlation Analysis for Key-Value Data with Local Differential Privacy [J]. Computer Science, 2021, 48(8): 278-283. |
[7] | ZHANG Xue-jun, YANG Hao-ying, LI Zhen, HE Fu-cun, GAI Ji-yang, BAO Jun-da. Differentially Private Location Privacy-preserving Scheme withSemantic Location [J]. Computer Science, 2021, 48(8): 300-308. |
[8] | CHEN Tian-rong, LING Jie. Differential Privacy Protection Machine Learning Method Based on Features Mapping [J]. Computer Science, 2021, 48(7): 33-39. |
[9] | WANG Le-ye. Geographic Local Differential Privacy in Crowdsensing:Current States and Future Opportunities [J]. Computer Science, 2021, 48(6): 301-305. |
[10] | PENG Chun-chun, CHEN Yan-li, XUN Yan-mei. k-modes Clustering Guaranteeing Local Differential Privacy [J]. Computer Science, 2021, 48(2): 105-113. |
[11] | WANG Mao-ni, PENG Chang-gen, HE Wen-zhu, DING Xing, DING Hong-fa. Privacy Metric Model of Differential Privacy via Graph Theory and Mutual Information [J]. Computer Science, 2020, 47(4): 270-277. |
[12] | LI Lan, YANG Chen, WANG An-fu. Study on Selection of Privacy Parameters ε in Differential Privacy Model [J]. Computer Science, 2019, 46(8): 201-205. |
[13] | HU Chuang, YANG Geng, BAI Yun-lu. Clustering Algorithm in Differential Privacy Preserving [J]. Computer Science, 2019, 46(2): 120-126. |
[14] | LI Sen-you, JI Xin-sheng, YOU Wei, ZHAO Xing. Hierarchical Control Strategy for Data Querying Based on Differential Privacy [J]. Computer Science, 2019, 46(11): 130-136. |
[15] | CUI Yi-hui, SONG Wei, PENG Zhi-yong, YANG Xian-di. Mining Method of Association Rules Based on Differential Privacy [J]. Computer Science, 2018, 45(6): 36-40. |
|