抗大数据分析的隐私保护：研究现状与进展

doi:10.11959/j.issn.2096-109x.2016.00042

网络与信息安全学报 ›› 2016, Vol. 2 ›› Issue (4): 44-55.doi: 10.11959/j.issn.2096-109x.2016.00042

抗大数据分析的隐私保护：研究现状与进展

仝伟^1,²,毛云龙^1,²,陈庆军^1,²,王彬入^1,²,张保佳^1,²,仲盛^1,²

¹ 南京大学计算机科学与技术系，江苏南京 210023
² 南京大学计算机软件新技术国家重点实验室，江苏南京 210023

修回日期:2016-04-03 出版日期:2016-04-01 发布日期:2016-05-25
作者简介:仝伟（1991-），男，江苏睢宁人，南京大学硕士生，主要研究方向为隐私保护与机制设计。|毛云龙（1990-），男，吉林安图人，南京大学博士生，主要研究方向为计算机网络、安全与隐私保护、无线网络。|陈庆军（1991-），男，重庆人，南京大学硕士生，主要研究方向为软件定义网络、移动感知中的隐私保护。|王彬入（1993-），男，江苏盐城人，南京大学硕士生，主要研究方向为隐私保护和安全博弈。|张保佳（1991-)，男，江苏沭阳人，南京大学硕士生，主要研究方向为数据完整性验证。|仲盛（1974-），男，江苏南京人，博士，南京大学教授、博士生导师，主要研究方向为密码学、博弈论及其在计算机网络、分布式系统中的应用。
基金资助:
国家自然科学基金资助项目(61321491);国家自然科学基金资助项目(61425024);国家自然科学基金资助项目(61300235);国家自然科学基金资助项目(61402223);江苏省双创计划基金资助项目

Survey of big-data-analysis-resistant privacy protection

Wei TONG^1,²,AOYun-long M^1,²,Qing-jun CEHN^1,²,Bin-ru WANG^1,²,Bao-jia ZHANG^1,²,Sheng ZHONG^1,²

¹ Department of Computer Science and Technology,Nanjing University,Nanjing 210023,China
² National Key Laboratory for Novel Software Technology,Nanjing University,Nanjing 210023,China

Revised:2016-04-03 Online:2016-04-01 Published:2016-05-25
Supported by:
The National Natural Science Foundation of China(61321491);The National Natural Science Foundation of China(61425024);The National Natural Science Foundation of China(61300235);The National Natural Science Foundation of China(61402223);Jiangsu Province Double Innovation Talent Program

摘要/Abstract

摘要：

隐私保护对于大数据时代的数据分享和利用起到了至关重要的作用。传统的隐私保护方法无法有效地应对在大数据环境中可能存在的数据间的深度关联带来的隐私泄露。因此，需要能够抗大数据分析的隐私保护方法。首先，调研了国内外学者的相关研究工作，并将当前和抗大数据分析的隐私保护相关的工作总结为海量高维异构数据隐私保护、地理位置隐私保护以及高可用性隐私保护发布方案3个方面。其次，着重介绍了南京大学COSEC研究团队在这方面取得的一些研究进展。最后，得到了抗大数据分析的隐私保护的重要性和前瞻性的结论，并介绍了未来可能的研究方向。

关键词: 隐私保护, 大数据, 差分隐私, 地理位置隐私

Abstract:

Privacy protection plays a significant role in big data era for data sharing and analysis.Traditional privacy protection approaches may not apply well for big data scenarios,because there may exist deep associations which can also cause privacy leakages.Therefore,privacy protection mechanisms that can defend against big data analysis is needed.A survey on related works was conducted,and the previous works were classified into three categories:privacy protection for massive high-dimensional heterogeneous data,location privacy protection and privacy protec-tion with enhanced utility.Then,the works in this area by COSEC group from nanjing university were introduced.At last,the privacy protection against big data analysis which was important and forward-looking was concluded,and the possible directions in this research area were introduced.

Key words: privacy protection, big data, differential privacy, location privacy

中图分类号:

TP309

仝伟,毛云龙,陈庆军,王彬入,张保佳,仲盛. 抗大数据分析的隐私保护：研究现状与进展[J]. 网络与信息安全学报, 2016, 2(4): 44-55.

Wei TONG,AOYun-long M,Qing-jun CEHN,Bin-ru WANG,Bao-jia ZHANG,Sheng ZHONG. Survey of big-data-analysis-resistant privacy protection[J]. Chinese Journal of Network and Information Security, 2016, 2(4): 44-55.

参考文献 71

[1]	The white house.Consumer data privacy:in a networked world[EB/OL]. .
[2]	European Commission.Proposal on general data protection regula-tion[R/OL]. .
[3]	LI N , ZHANG N , DAS S K , et al . Privacy preservation in wireless sensor networks:a state-of-the-art survey[J]. Ad Hoc Networks, 2009,7(8): 1501-1514.
[4]	DING X , ZHANG L , WAN Z , et al . A brief survey on de-anonymization attacks in online social networks[C]// 2010 In-ternational Conference on Computational Aspects of Social Net-works (CASoN),IEEE.c 2010:611-615.
[5]	BACKSTROM L , DWORK C , KLEINBERG J . Wherefore art thou r3579x? anonymized social networks,hidden patterns,and struc-tural steganography[C]// International Conference on World Wide Web.c 2007:181-190.
[6]	NARAYANAN A , SHMATIKOV V . De-anonymizing social net-works[C]// 2009 30th IEEE Symposium on Security and Privacy,IEEE.c 2009:173-187.
[7]	WONDRACEK G , HOLZ T , KIRDA E , et al . A practical attack to de-anonymize social network users[C]// 2010 IEEE Symposium on Security and Privacy (SP).c 2010:223-238.
[8]	HAY M , MIKLAU G , JENSEN D , et al . Resisting structural re-identification in anonymized social networks[J]. The VLDB En-dowment, 2008,1(1):102-114.
[9]	NARAYANAN A , SHMATIKOV V . Robust de-anonymization of large sparse datasets[C]// 2008 IEEE Symposium on Security and Privacy(SP).c 2008:111-125.
[10]	NAVEED M , AYDAY E , CLAYTON E W , et al . Privacy in the genomic era[J]. ACM Computing Surveys (CSUR), 2015,48(1): 6.
[11]	TRAMèR F , HUANG Z , HUBAUX J P , et al . Differential privacy with bounded priors:reconciling utility and privacy in genome-wide association studies[C]// The 22nd ACM Sigsac Conference on Com-puter and Communications Security.c 2015:1286-1297.
[12]	JOHNSON A , SHMATIKOV V . Privacy-preserving data explora-tion in genome-wide association studies[C]// The 19th ACM Sigkdd International Conference on Knowledge Discovery and Data Min-ing.c 2013:1079-1087.
[13]	LI N , QARDAJI W , SU D , et al . Membership privacy:a unifying framework for privacy definitions[C]// The 2013 ACM Sigsac Con-ference on Computer ＆ communications security.c 2013:889-900.
[14]	刘华玲, 郑建国, 孙辞海 . 基于贪心扰动的社交网络隐私保护研究[J]. 电子学报 2013(8):1586-1591.
	LIU H L , ZHENG J G , SUN C H . Privacy preserving in social net-works based on greedy perturbation[J]. Journal of Electron-ics, 2013,08:1586-1591.
[15]	刘华玲, 郑建国, 孙辞海 . 社交网络隐私保护中的随机算法[J]. 信息与控制 2012(4):197-201.
	LIU H L , ZHENG J G , SUN C H . Randomized algorithm for pri-vacy preservation in social networks[J]. Information and Control, 2012(4):197-201.
[16]	吕志泉, 洪澄, 张敏 , 等. 面向社交网络的隐私保护方案[J]. 通信学报 2014(8):23-32.
	LV Z Q , HONG C , ZHANG M , et al . Privacy-preserving scheme for social networks[J]. Journal of Communications, 2014(8):23-32.
[17]	KIDO H , YANAGISAWA Y , SATOH T . An anonymous communi-cation technique using dummies for location-based services[C]// 2005 International Conference on Pervasive Services(ICPS'05).c 2005:88-97.
[18]	MOKBEL M F . Privacy in location-based services:state-of-the-art and research directions[C]// 2007 International Conference on Mo-bile Data Management.c 2007:228-228.
[19]	DOMINGO-FERRER J , SRAMKA M , TRUJILLO-RASúA R . Privacy-preserving publication of trajectories using microaggrega-tion[C]// The 3rd ACM SIGSPATIAL International Workshop on Security and Privacy in GIS and LBS.c 2010:26-33.
[20]	GRUTESER M , LIU X . Protecting privacy in continuous loca-tion-tracking applications[J]. IEEE Security ＆ Privacy, 2004(2):28-34.
[21]	DWORK C . Differential privacy[M]// Automata,languages and programming . Berlin Heidelberg: Springer, 2006:1-12.
[22]	LEE B , OH J , YU H , et al . Protecting location privacy using loca-tion semantics[C]// The 17th ACM Sigkdd International Conference on Knowledge Discovery and Data Mining.c 2011:1289-1297.
[23]	ANDRéS M E , BORDENABE N E . CHATZIKOKOL-AKIS K,et al.Geo-indistinguishability:differential privacy for location-based systems[C]// 2013 ACM Sigsac Conference on Computer ＆ Com-munications Security.c 2013:901-914.
[24]	CHATZIKOKOLAKIS K , ANDRéS M E , BORDENABE N E , et al . Broadening the scope of differential privacy using met-rics[C]// Privacy Enhancing Technologies.c 2013:82-102.
[25]	CHATZIKOKOLAKIS K , PALAMIDESSI C , STRONATI M . A predictive differentially-private mechanism for mobility traces[C]// Privacy Enhancing Technologies.c 2014:21-41.
[26]	XIAO Y , XIONG L . Protecting locations with differential privacy under temporal correlations[C]// The 22nd ACM Sigsac Conference on Computer and Communications Security.c 2015:1298-1309.
[27]	BORDENABE N E , CHATZIKOKOLAKIS K , PALAMIDESSI C . Optimal geo-indistinguishable mechanisms for location pri-vacy[C]// 2014 ACM Sigsac Conference on Computer and Com-munications Security.c 2014:251-262.
[28]	霍峥, 孟小峰, 黄毅 . PrivateCheckIn:一种移动社交网络中的轨迹隐私保护方法[J]. 计算机学报 2013(4):716-726.
	HUO Z , MENG X F , HUANG Y . PrivateCheckIn:trajectory pri-vacy-preserving for check-in services in MSNS[J]. Chinese Journal of Computers, 2013(4):716-726.
[29]	赵婧, 张渊, 李兴华 , 等. 基于轨迹频率抑制的轨迹隐私保护方法[J]. 通信学报 2014(10):2096-2106.
	ZHAO J , ZHANG Y , LI X H , et al . A trajectory privacy protection approach via trajectory frequency suppression[J]. Chinese Journal of Computers, 2014(10):2096-2106.
[30]	吴英杰, 唐庆明, 倪巍伟 , 等. 基于聚类杂交的隐私保护轨迹数据发布算法[J]. 计算机研究与发展 2011(5):：578-593.
	WU Y J , TANG Q M , NI W W , et al . A clustering hybrid based al-gorithm for privacy preserving trajectory data publishing[J]. Jour-nal of Computer Research and Development, 2011(5):：578-593.
[31]	AGRAWAL R , SRIKANT R . Privacy-preserving data mining[J]. ACM Sigmod Record, 2000,29(2):439-450.
[32]	OLIVEIRA S R M , ZAIANE O R . Privacy preserving frequent itemset mining[C]// The IEEE international Conference on Privacy,Security and Data Mining.c c2002:43-54.
[33]	SAYGIN Y , VERYKIOS V S , ELMAGARMID A K . Privacy pre-serving association rule mining[C]// International Workshop on Research Issues in Data Engineering:Engineering E-commerce/E-business Systems (RIDE-2EC).c 2002,41(2): 151-158.
[34]	SAMARATI P , SWEENEY L . Generalizing data to provide ano-nymity when disclosing information[C]// The 17th ACM Sigact-sigmod-sigart Symposium on Principles of Database Systems.c 1998,188.
[35]	SWEENEY L . K-anonymity:A model for protecting privacy[J]. International Journal of Uncertainty,Fuzziness and Knowl-edge-Based Systems, 2002,10(05):557-570.
[36]	MACHANAVAJJHALA A , KIFER D , GEHRKE J , et al . L-diversity:privacy beyond k-anonymity[J]. ACM Transactions on Knowledge Discovery from Data (TKDD), 2007,1(1):3.
[37]	LI N , LI T , VENKATASUBRAMANIAN S . T-closeness:privacy beyond k-anonymity and l-diversity[C]// IEEE 23rd International Con-ference on Data Engineering(ICDE).c 2007:106-115.
[38]	ZHANG Y , MAO D , ZHANG H , et al . Privacy preserving market schemes for mobile sensing[C]// 2015 44th International Conference on Parallel Processing (ICPP).c 2015:909-918.
[39]	HUA J , TANG A , ZHONG S . Advertiser and publisher-centric privacy aware online behavioral advertising[C]// IEEE 35th Interna-tional Conference on Distributed Computing Systems (ICDCS).c 2015:298-307.
[40]	HUA Y , MAO D , ZHANG H , et al . Privacy-preserving utility verifi-cation of the data published by non-interactive differentially private mechanisms[J]. IEEE Transactions on Information Forensics ＆Security, 2016.
[41]	CANNY J . Collaborative filtering with privacy[C]// 2002 IEEE Symposium on Security and Privacy.c 2002:45-57.
[42]	KOREN Y , BELL R , VOLINSKY C , et al . Matrix factorization tech-niques for recommender systems[J]. Computer, 2009(8):30-37.
[43]	HUA J , XIA C , ZHONG S . Differentially private matrix factoriza-tion[C]// The 24th International Conference on Artificial Intelli-gence(IJCAI).c 2015:1763-1770.
[44]	CAO J , CONG G , JENSEN C S . Differentially private matrix factoriza-tion[J]. The VLDB Endowment, 2010,3(1/2):1009-1020.
[45]	ZHENG Y , ZHANG L , XIE X , et al . Mining interesting locations and travel sequences from GPS trajectories[C]// The 18th Interna-tional Conference on World Wide Web.c 2009:791-800.
[46]	CLARKE R . Person location and person tracking-technologies,risks and policy implications[J]. Information Technology ＆ People, 2001,14(2):206-231.
[47]	PELLETIER M P , TREPANIER M , MORENCY C . Smart card data use in public transit:a literature review[J]. Transportation Research Part C:Emerging Technologies, 2011,19(4): 557-568.
[48]	HUA J , GAO Y , ZHONG S . Differentially private publication of general time-serial trajectory data[C]// 2015 IEEE Conference on Computer Communications (INFOCOM).c 2015:549-557.
[49]	MAO Y , CHEN T , ZHANG Y , et al . Protecting location information in collaborative sensing of cognitive radio networks[C]// The 18th ACM International Conference on Modeling,Analysis and Simula-tion of Wireless and Mobile Systems.c 2015:219-226.
[50]	ZHONG S , YAO H . Towards cheat-proof cooperative relayfor cognitive radio networks[J]. IEEE Transactions on Parallel and Dis-tributed Systems, 2014,25(9):2442-2451.
[51]	CHEN T , ZHONG S . Truthful auctions for continuous spectrum with variable bandwidths[J]. IEEE Transactions on Wireless Com-munications, 2014,13(2):1116-1128.
[52]	HUA D , DU T , ZHONG S . Towards attack-resistant peer-assisted indoor localization[M]// Computer Security—ESORICS 2015.. Springer International Publishing, 2015:417-437.
[53]	HERRING R , HOFLEITNER A , WORK D , et al . Mobile millen-nium-participatory traffic estimation using mobile phones[C]// CPS Forum,Cyber-Physical Systems Week.c 2009.
[54]	THIAGARAJAN A , RAVINDRANATH L , LACURTS K , et al . VTrack:accurate,energy-aware road traffic delay estimation using mobile phones[C]// CPS Forum,Cyber-Physical Systems Week.c 2009.
[55]	DAS T , MOHAN P , PADMANABHAN V N , et al . PRISM:plat-form for remote sensing using smartphones[C]// The 8th Interna-tional Conference on Mobile Systems,Applications,and Services,ACM.c 2010:63-76.
[56]	RANA R K , CHOU C T , KANHERE S S , et al . Ear-phone:an end-to-end participatory urban noise mapping system[C]// The 9th ACM International Conference on Information Processing in Sen-sor Networks.c 2010:105-116.
[57]	BAO X , CHOUDHURY R R . Movi:mobile phone based video highlights via collaborative sensing[C]// The 8th International Con-ference on Mobile Systems,Applications,and Services,ACM.c 2010:357-370.
[58]	ZHANG Y , CHEN Q , ZHONG S . Efficient and privacy-preserving min and k-th min computations in mobile sensing systems[J]. IEEE Transactions on Dependable and Secure Computing, 2015.
[59]	LI Q , CAO G . Efficient and privacy-preserving data aggregation in mobile sensing[C]// 2012 20th IEEE International Conference on Network Protocols (ICNP).c 2012:1-10.
[60]	ZHANG Y , CHEN Q , ZHONG S . Privacy-preserving data aggrega-tion in mobile phone sensing[J]. IEEE Transactions on Information Forensics and Security, 2016.
[61]	ZHANG Y , ZHANG H , TANG S , et al . Designing secure and de-pendable mobile sensing mechanisms with revenue guarantees[J]. IEEE Transactions on Information Forensics and Security, 2016,11(1): 100-113.
[62]	HAO Z , MAO Y , ZHONG S , et al . Toward wireless security with-out computational assumptions—oblivious transfer based on wire-less channel characteristics[J]. IEEE Transactions on Computers, 2014,63(6): 1580-1593.
[63]	DU S , HUA J , GAO Y , et al . EV-linker:mapping eavesdropped Wi-Fi packets to individuals via electronic and visual signal matching[J]. Journal of Computer and System Sciences, 2016,82(1): 156-172.
[64]	ZHONG S , ZHANG Y . How to select optimal gateway in multi-domain wireless networks:alternative solutions without learning[J]. IEEE Transactions on Wireless Communications, 2013,12(11):5620-5630.
[65]	KATTA N P , REXFORD J , WALKER D . Incremental consistent updates[C]// ACM Sigcomm Workshop on Hot Topics in Software Defined Networking.c 2013:49-54.
[66]	MAHAJAN R , WATTENHOFER R . On consistent updates in soft-ware defined networks[C]// ACM Sigcomm Workshop on Hot Top-ics in Software Defined Networking.c 2013:20.
[67]	MCGEER R . A safe,efficient update protocol for OpenFlow net-works[C]// ACM Sigcomm Workshop on Hot Topics in Software Defined Networking.c 2012:61-66.
[68]	REITBLATT M , FOSTER N , REXFORD J , et al . Abstractions for network update[J]. ACM Sigcomm Computer Communication Re-view, 2012,42(4): 323-334.
[69]	HUA J , GE X , ZHONG S . Foum:a flow-ordered consistent update mechanism for software-defined networking in adversarial set-tings[C]// IEEE International Conference on Computer Communi-cations (INFOCOM).c 2016.
[70]	JAIN S , KUMAR A , MANDAL S , et al . B4:experience with a globally-deployed software defined WAN[J]. ACM Sigcomm Computer Communication Review, 2013,43(4): 3-14.
[71]	CHEN Q , QIAN C , ZHONG S . Privacy-preserving cross-domain routing optimization--a cryptographic approach[C]// IEEE Interna-tional Conference on Network Protocols(ICNP).c 2015:356-365.

抗大数据分析的隐私保护：研究现状与进展

Survey of big-data-analysis-resistant privacy protection

在线阅读

pdf下载

可视化

摘要/Abstract

引用本文

使用本文

参考文献 71

相关文章 15

Metrics

推荐阅读 0

[1]	陈赛特, 李卫海, 姚远志, 俞能海. 轻量级K匿名增量近邻查询位置隐私保护算法[J]. 网络与信息安全学报, 2023, 9(3): 60-72.
[2]	余锋, 林庆新, 林晖, 汪晓丁. 基于生成对抗网络的隐私增强联邦学习方案[J]. 网络与信息安全学报, 2023, 9(3): 113-122.
[3]	肖敏, 毛发英, 黄永洪, 曹云飞. 基于属性签名的车载网匿名信任管理方案[J]. 网络与信息安全学报, 2023, 9(2): 33-45.
[4]	许建龙, 林健, 黎宇森, 熊智. 分布式用户隐私保护可调节的云服务个性化QoS预测模型[J]. 网络与信息安全学报, 2023, 9(2): 70-80.
[5]	孙哲, 宁洪, 殷丽华, 方滨兴. 基于教学实训靶场的“数据隐私保护”课程建设初探[J]. 网络与信息安全学报, 2023, 9(1): 178-188.
[6]	白雪, 秦宝东, 郭瑞, 郑东. 基于SM2的两方协作盲签名协议[J]. 网络与信息安全学报, 2022, 8(6): 39-51.
[7]	肖敏, 姚涛, 刘媛妮, 黄永洪. 具有隐私保护的动态高效车载云管理方案[J]. 网络与信息安全学报, 2022, 8(6): 70-83.
[8]	李东, 郝艳妮, 彭升辉, 訾瑞杰, 刘西蒙. 国家自然科学基金委员会网络安全现状与展望[J]. 网络与信息安全学报, 2022, 8(6): 92-101.
[9]	卢晨昕, 陈兵, 丁宁, 陈立全, 吴戈. 具有紧凑标签的基于身份匿名云审计方案[J]. 网络与信息安全学报, 2022, 8(6): 156-168.
[10]	明盛智, 朱建明, 隋智源, 张娴. 信息增值机制下在线医疗隐私保护策略[J]. 网络与信息安全学报, 2022, 8(6): 169-177.
[11]	单棣斌, 杜学绘, 王文娟, 刘敖迪, 王娜. 基于GNN双源学习的访问控制关系预测方法[J]. 网络与信息安全学报, 2022, 8(5): 40-55.
[12]	应作斌, 方一晨, 张怡文. 动态聚合权重的隐私保护联邦学习框架[J]. 网络与信息安全学报, 2022, 8(5): 56-65.
[13]	穆超, 王鑫, 杨明, 张恒, 陈振娅, 吴晓明. 面向物联网设备固件的硬编码漏洞检测方法[J]. 网络与信息安全学报, 2022, 8(5): 98-110.
[14]	张娴, 朱建明, 隋智源, 明盛智. 数字货币交易匿名性与监管的博弈分析[J]. 网络与信息安全学报, 2022, 8(5): 150-157.
[15]	刘峰, 杨杰, 齐佳音. 区块链密码学隐私保护技术综述[J]. 网络与信息安全学报, 2022, 8(4): 29-44.