Paillier加密的隐私保护群智感知任务发布算法

doi:10.3778/j.issn.1673-9418.2012037

计算机科学与探索 ›› 2022, Vol. 16 ›› Issue (6): 1327-1333.DOI: 10.3778/j.issn.1673-9418.2012037

Paillier加密的隐私保护群智感知任务发布算法

田静, 杜云明, 李帅, 刘义()

佳木斯大学信息电子技术学院,黑龙江佳木斯 154000

收稿日期:2020-12-10 修回日期:2021-03-04 出版日期:2022-06-01 发布日期:2021-03-24
通讯作者: + E-mail: jmsdxlytj@163.com
作者简介:田静（1980—）,女,黑龙江佳木斯人,硕士,讲师,主要研究方向为数字信号处理、模式识别。
杜云明（1977—）,男,黑龙江佳木斯人,硕士,副教授,主要研究方向为机器视觉、图像处理等。
李帅（1976—）,女,黑龙江佳木斯人,实验师,主要研究方向为数字信号处理、模式识别等。
刘义（1979—）,男,黑龙江佳木斯人,硕士,讲师,CCF会员,主要研究方向为数据分析、虹膜识别等。
基金资助:
黑龙江省省属高等学校基本科研业务费基础研究项目(2020-KYYWF-0227)

Paillier Homomorphic Encryption Based Location Privacy Protection Scheme for Crowdsensing Task Distribution

TIAN Jing, DU Yunming, LI Shuai, LIU Yi()

College of Information Science and Electronic Technique, Jiamusi University, Jiamusi, Heilongjiang 154000, China

Received:2020-12-10 Revised:2021-03-04 Online:2022-06-01 Published:2021-03-24
About author:TIAN Jing, born in 1980, M.S., lecturer. Her research interests include digital signal processing and pattern recognition.
DU Yunming, born in 1977, M.S., associate professor. His research interests include machine vision, image processing, etc.
LI Shuai, born in 1976, experimentalist. Her research interests include digital signal processing, pattern recognition, etc.
LIU Yi, born in 1979, M.S., lecturer, member of CCF. His research interests include data analysis, iris image recognition, etc.
Supported by:
Basic Scientific Research Operating Expenses of Heilongjiang Provincial Universities and Colleges(2020-KYYWF-0227)

摘要/Abstract

摘要：

针对群智感知任务发布过程中,任务申请者、任务发布者以及授权机构可彼此获知位置隐私的问题,基于Paillier公钥密码系统的同态特性,提出了一种有效保障参与群智感知任务各实体间位置隐私的保护算法。该算法通过对可参与以及发布任务位置网格单元的密态环境的同态计算,完成对任务位置和响应位置的秘密匹配,从而实现位置隐私保护下的群智感知任务发布。最后,通过安全性分析,对所提出的任务发布方法从理论上加以分析证明,同时利用模拟环境的任务发布,对所提算法进行了实验验证,并在同条件下与同类算法进行比较,其结果进一步明确了所提算法的优势。

关键词: 群智感知, 同态加密, 位置隐私, 隐私保护, 任务发布

Abstract:

In order to solve the problem that applicants, publishers and authorized agencies can know the location privacy of each other in the process of task publication of swarm intelligence, based on the homomorphism of Paillier public key cryptosystem, an effective protection algorithm is proposed to guarantee the location privacy of each entity participating in swarm intelligence task. The algorithm achieves the secret matching of task position and response position through homomorphism calculation of the dense environment in which the task position grid unit can participate and publish, so as to realize the group intelligence perception task distribution under the protection of position privacy. Finally, through security analysis, the proposed task distribution method is theoretically analyzed and proven, and the proposed algorithm is experimentally verified by using task distribution in simulated environment. Compared with similar algorithms under the same conditions, the results further clarify the advantages of the proposed algorithm.

Key words: crowdsensing, homomorphic encryption, location privacy, privacy protection, task distribution

中图分类号:

TP309.2

田静, 杜云明, 李帅, 刘义. Paillier加密的隐私保护群智感知任务发布算法[J]. 计算机科学与探索, 2022, 16(6): 1327-1333.

TIAN Jing, DU Yunming, LI Shuai, LIU Yi. Paillier Homomorphic Encryption Based Location Privacy Protection Scheme for Crowdsensing Task Distribution[J]. Journal of Frontiers of Computer Science and Technology, 2022, 16(6): 1327-1333.

图/表 6

图1 群智感知的系统架构

Fig.1 System architecture of crowdsensing

图2 不同算法的执行时间

Fig.2 Running time of various algorithms

图3 不同算法的感知位置匹配率

Fig.3 Matching probability of crowdsensing locations of various algorithms

图4 不同算法的反馈结果正确率

Fig.4 Accuracy of feedback results of various algorithms

图5 不同算法猜测实体位置的成功率（攻击者）

Fig.5 Success ratio of guessing real locations of various algorithms (adversary)

图6 不同算法的实体间信息披露

Fig.6 Entropy of information disclosure of various algorithms

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Paillier加密的隐私保护群智感知任务发布算法

Paillier Homomorphic Encryption Based Location Privacy Protection Scheme for Crowdsensing Task Distribution

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