移动社交网络中面向隐私保护的精确好友匹配

doi:10.11959/j.issn.1000-436x.2022208

通信学报 ›› 2022, Vol. 43 ›› Issue (11): 90-103.doi: 10.11959/j.issn.1000-436x.2022208

移动社交网络中面向隐私保护的精确好友匹配

彭滔¹, 钟文韬¹, 王国军¹, 罗恩韬², 熊金波³, 刘忆宁⁴, Hao Wang⁵

¹ 广州大学计算机科学与网络工程学院，广东广州 510006
² 湖南科技学院信息工程学院，湖南永州 425000
³ 福建师范大学计算机与网络空间安全学院，福建福州 350117
⁴ 桂林电子科技大学计算机与信息安全学院，广西桂林 541000
⁵ 挪威科技大学计算机科学学院，挪威约维克 2815

修回日期:2022-10-18 出版日期:2022-11-25 发布日期:2022-11-01
作者简介:彭滔（1982− ），女，湖南长沙人，博士，广州大学副教授、硕士生导师，主要研究方向为移动群智感知网、社交网络隐私保护、云计算安全、区块链技术
钟文韬（1998− ），男，云南曲靖人，广州大学硕士生，主要研究方向为移动群智感知网、社交网络隐私保护
王国军（1970− ），男，湖南长沙人，博士，广州大学教授、博士生导师，主要研究方向为人工智能、区块链、网络安全、隐私保护
罗恩韬（1978− ），男，湖南永州人，博士，湖南科技学院教授、硕士生导师，主要研究方向为移动社交网络、机器学习、边缘计算的安全与隐私保护等
熊金波（1981− ），男，湖南益阳人，博士，福建师范大学教授、博士生导师，主要研究方向为云数据安全与隐私保护、移动数据安全、大数据安全
刘忆宁（1973− ），男，河南巩义人，博士，桂林电子科技大学教授、博士生导师，主要研究方向为轻量级安全协议
Hao Wang（1978− ），男，挪威科技大学教授、博士生导师，主要研究方向为大数据、知识管理、工业物联网、高性能计算、可信系统
基金资助:
国家自然科学基金资助项目(U1905211);国家自然科学基金资助项目(62272102);国家自然科学基金资助项目(61872088);国家自然科学基金资助项目(62072133);国家自然科学基金资助项目(62172159);国家重点研发计划基金资助项目(2020YFB1005804);湖南省自然科学基金资助项目(2021JJ30294)

Privacy-preserving precise profile matching in mobile social network

Tao PENG¹, Wentao ZHONG¹, Guojun WANG¹, Entao LUO², Jinbo XIONG³, Yining LIU⁴, Wang Hao⁵

¹ School of Computer Science and Cyber Engineering, Guangzhou University, Guangzhou 510006, China
² School of Information Engineering, Hunan University of Science and Engineering, Yongzhou 425000, China
³ School of Computer and Cyber Security, Fujian Normal University, Fuzhou 350117, China
⁴ School of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin 541000, China
⁵ Department of Computer Science, Norwegian University of Science and Technology, Gj?vik 2815, Norway

Revised:2022-10-18 Online:2022-11-25 Published:2022-11-01
Supported by:
The National Natural Science Foundation of China(U1905211);The National Natural Science Foundation of China(62272102);The National Natural Science Foundation of China(61872088);The National Natural Science Foundation of China(62072133);The National Natural Science Foundation of China(62172159);The National Key Research and Development Program of China(2020YFB1005804);Hunan Provincial Natural Science Foundation(2021JJ30294)

摘要/Abstract

摘要：

好友匹配通过比较用户间属性相似度向交友请求者推荐好友，是移动社交网络应用中的核心功能。然而，在好友匹配的过程中，用户个人信息很可能会被服务器或者其他恶意用户窃取导致隐私泄露，且现有方案存在匹配结果不精确或者无法满足用户多维度隐私保护需求等挑战。基于此，提出面向隐私保护的精确好友匹配（P3M）方案，查询者可以根据自身需求灵活设定特征属性和距离的匹配范围。利用可比较内积编码（CIPE）和Paillier加密算法对用户属性和查询范围进行编码和加密，并设计安全点积协议实现用户属性和查询范围的安全比较。相较于现有方案， P3M 方案支持查询者自定义查询范围以获得精确的查询结果，综合考虑用户特征属性及位置属性等多维度的隐私保护。最后，对P3M的正确性和安全性进行详细分析和证明，并通过实验验证P3M方案的有效性和高效性。

关键词: 隐私保护, 移动社交网络, 好友匹配, 保序加密

Abstract:

Profile matching is a key feature in mobile social networking applications, where friends are recommended to requesters by comparing the similarity of attributes between them.However, users’ personal information is exposed to the risk of privacy disclosure in the process of profile matching.The existing solutions exist some issues such as inaccurate matching results or inability to meet users’ requirements for multi-dimensional privacy protection.Baesed on this, a privacy-preserving precise profile matching (P3M) scheme was proposed, which allowed users to flexibly set the matching range of attributes and distances according to their requirements.The Paillier encryption was utilized to ensure data security of users, and a secure dot product protocol was designed to achieve secure ciphertext comparison of user attributes and query ranges.The P3M realized multi-dimensional privacy-preserving of users including user feature attributes and location attributes.Finally, the correctness and security of P3M scheme were analyzed and proved in detail, and extensive experimental results verified the effectiveness and efficiency of P3M scheme.

Key words: privacy-preserving, mobile social network, profile matching, order-preserving encryption

中图分类号:

TN92

彭滔, 钟文韬, 王国军, 罗恩韬, 熊金波, 刘忆宁, Hao Wang. 移动社交网络中面向隐私保护的精确好友匹配[J]. 通信学报, 2022, 43(11): 90-103.

Tao PENG, Wentao ZHONG, Guojun WANG, Entao LUO, Jinbo XIONG, Yining LIU, Wang Hao. Privacy-preserving precise profile matching in mobile social network[J]. Journal on Communications, 2022, 43(11): 90-103.

图/表 10

图1

表1

符号描述"

参数	含义
$D$	所有用户的数据
$A_{i}$	第i位用户的属性集合
$Q_{j}$	查询者为用户 j设定的查询范围的集合
$T_{Q}_{{_{j}}_{i}}$	用户 j的第i个属性对应的安全查询向量
$T_{Q_{j}}$	用户 j所有属性对应的安全查询向量的集合
$I_{i_{k}}$	用户i的第k 个属性对应的安全索引向量
$I_{i}$	用户i所有属性对应的安全索引向量的集合
k	Paillier加密算法安全参数
L	用于CIPE的随机比特串
d	比特串L 的长度（d 为偶数）
$p_{i_{k}}$	用户i的第k 个属性由CIPE所得向量
${\hat{p}}_{i_{k}}$	使用Paillier对 $p_{i_{k}}$ 中每个元素加密后所得向量
$q_{j_{k, ϕ}}$	用户 j的第k 个属性所对应查询范围的CIPE向量
${\hat{q}}_{j_{k, ϕ}}$	使用Paillier对 $q_{j_{k, ϕ}}$ 中每个元素加密后所得向量

表1

图2

图3

图4

图5

图6

图7

表2

图8

参考文献 29

[1]	FREEDMAN M J , HAZAY C , NISSIM K ,et al. Efficient set intersection with simulation-based security[J]. Journal of Cryptology, 2016,29(1): 115-155.
[2]	GAO C Z , CHENG Q , LI X ,et al. Cloud-assisted privacy-preserving profile-matching scheme under multiple keys in mobile social network[J]. Cluster Computing, 2019,22(1): 1655-1663.
[3]	ATENIESE G , FRANCATI D , NU?EZ D , ,et al. Match me if you can:matchmaking encryption and its applications[J]. Journal of Cryptology, 2021,34(3): 1-50.
[4]	YI X , BERTINO E , RAO F Y ,et al. Privacy-preserving user profile matching in social networks[J]. IEEE Transactions on Knowledge and Data Engineering, 2020,32(8): 1572-1585.
[5]	LIU Q , WU S X , PEI S Y ,et al. Secure and efficient multi-attribute range queries based on comparable inner product encoding[C]// Proceedings of 2018 IEEE Conference on Communications and Network Security. Piscataway:IEEE Press, 2018: 1-9.
[6]	AGRAWAL R , EVFIMIEVSKI A , SRIKANT R . Information sharing across private databases[C]// Proceedings of the 2003 ACM SIGMOD International Conference on Management of Data. New York:ACM Press, 2003: 86-97.
[7]	VON ARB M , BADER M , KUHN M ,et al. VENETA:serverless friend-of-friend detection in mobile social networking[C]// Proceedings of 2008 IEEE International Conference on Wireless and Mobile Computing,Networking and Communications. Piscataway:IEEE Press, 2008: 184-189.
[8]	MAHMOUD M , RABIEH K , SHERIF A ,et al. Privacy-preserving fine-grained data retrieval schemes for mobile social networks[J]. IEEE Transactions on Dependable and Secure Computing, 2019,16(5): 871-884.
[9]	LUO E T , GUO K H , TANG Y Y ,et al. Hidden the true identity and dating characteristics based on quick private matching in mobile social networks[J]. Future Generation Computer Systems, 2020,109: 633-641.
[10]	SHEN H J , ZHOU J , CAO Z F ,et al. Blockchain-based lightweight certificate authority for efficient privacy-preserving location-based service in vehicular social networks[J]. IEEE Internet of Things Journal, 2020,7(7): 6610-6622.
[11]	LI J , ZENG F Z , XIAO Z ,et al. Drive2friends:inferring social relationships from individual vehicle mobility data[J]. IEEE Internet of Things Journal, 2020,7(6): 5116-5127.
[12]	PENG T , LIU Q , WANG G J ,et al. Multidimensional privacy preservation in location-based services[J]. Future Generation Computer Systems, 2019,93: 312-326.
[13]	LIU Q , HOU P L , WANG G J ,et al. Intelligent route planning on large road networks with efficiency and privacy[J]. Journal of Parallel and Distributed Computing, 2019,133: 93-106.
[14]	LIU Q , PENG Y , WU J ,et al. Secure multi-keyword fuzzy searches with enhanced service quality in cloud computing[J]. IEEE Transactions on Network and Service Management, 2021,18(2): 2046-2062.
[15]	LIU Q , PENG Y , PEI S Y ,et al. Prime inner product encoding for effective wildcard-based multi-keyword fuzzy search[J]. IEEE Transactions on Services Computing, 2022,15(4): 1799-1812.
[16]	李宇溪, 周福才, 徐紫枫 . 支持K-近邻搜索的移动社交网络隐私保护方案[J]. 计算机学报, 2021,44(7): 1481-1500.
	LI Y X , ZHOU F C , XU Z F . Privacy preserving K-nearest-neighbor search over mobile social network[J]. Chinese Journal of Computers, 2021,44(7): 1481-1500.
[17]	崔炜荣, 杜承烈 . 社交网络中基于CP-ABE的隐私保护属性匹配方法[J]. 计算机应用, 2018,38(4): 1051-1057.
	CUI W R , DU C L . Privacy preserving attribute matching method based on CP-ABE in social networks[J]. Journal of Computer Applications, 2018,38(4): 1051-1057.
[18]	LUO E T , LIU Q , ABAWAJY J H ,et al. Privacy-preserving multi-hop profile-matching protocol for proximity mobile social networks[J]. Future Generation Computer Systems, 2017,68: 222-233.
[19]	SAMANTHULA B K , ELMEHDWI Y , HOWSER G ,et al. A secure data sharing and query processing framework via federation of cloud computing[J]. Information Systems, 2015,48: 196-212.
[20]	XU G Q , LIU B Y , JIAO L T ,et al. Trust2Privacy:a novel fuzzy trust-to-privacy mechanism for mobile social networks[J]. IEEE Wireless Communications, 2020,27(3): 72-78.
[21]	LI F H , HE Y Y , NIU B ,et al. Small-world:secure friend matching over physical world and social networks[J]. Information Sciences, 2017,387: 205-220.
[22]	ZHANG L , LI X Y , LIU K B ,et al. Message in a sealed bottle:privacy preserving friending in mobile social networks[J]. IEEE Transactions on Mobile Computing, 2014,14(9): 1888-1902.
[23]	PENG T , GUAN K , LIU J ,et al. A blockchain-based mobile crowdsensing scheme with enhanced privacy[J]. Concurrency and Computation:Practice and Experience, 2021:doi.org/10.1002/cpe.6664.
[24]	PENG T , GUAN K , LIU J . A privacy-preserving mobile crowdsensing scheme based on blockchain and trusted execution environment[J]. The IEICE Transactions on Information and Systems,2021:doi.org/10.1587/transinf. 2021BCP0001.
[25]	DING X F , WANG Z , ZHOU P ,et al. Efficient and privacy-preserving multi-party skyline queries over encrypted data[J]. IEEE Transactions on Information Forensics and Security, 2021,16: 4589-4604.
[26]	LIU L , CHEN R M , LIU X M ,et al. Towards practical privacy-preserving decision tree training and evaluation in the cloud[J]. IEEE Transactions on Information Forensics and Security, 2020,15: 2914-2929.
[27]	PENG T , LIU Q , MENG D ,et al. Collaborative trajectory privacy preserving scheme in location-based services[J]. Information Sciences, 2017,387: 165-179.
[28]	LIU Q , TIAN Y , WU J ,et al. Enabling verifiable and dynamic ranked search over outsourced data[J]. IEEE Transactions on Services Computing, 2022,15(1): 69-82.
[29]	WANG J . Encyclopedia of data warehousing and mining[M]. Hershey: IGI Global, 2005.

方案	中心化架构	匹配过程不需要用户参与	细粒度匹配	设定匹配范围	考虑位置范围
文献[2]方案	√	√	√	×	×
文献[4]方案	√	√	×	×	×
文献[9]方案	√	×	×	×	√
文献[10]方案	√	×	×	×	×
文献[11]方案	√	√	×	×	×
P3M方案	√	√	√	√	√

移动社交网络中面向隐私保护的精确好友匹配

Privacy-preserving precise profile matching in mobile social network

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