华南理工大学学报(自然科学版) ›› 2020, Vol. 48 ›› Issue (8): 38-48.doi: 10.12141/j.issn.1000-565X.190722

• 电子、通信与自动控制 • 上一篇    下一篇

属性感知的 MCS 任务分配与隐私保护协同机制

杨鹏1,2 吴其明1,2   

  1. 1. 重庆邮电大学 通信与信息工程学院∥泛在感知与互联重庆市重点实验室,重庆 400065;2. 工信部中国信息通信研究院西部分院,重庆 401336
  • 收稿日期:2019-10-15 修回日期:2020-02-01 出版日期:2020-08-25 发布日期:2020-08-01
  • 通信作者: 杨鹏(1980-),男,高级工程师,主要从事下一代移动通信技术研究。 E-mail:yangpeng@caict. ac. cn
  • 作者简介:杨鹏(1980-),男,高级工程师,主要从事下一代移动通信技术研究。
  • 基金资助:
    国家自然科学基金资助项目 (61771082,61871062); 重庆市高校创新团队建设计划项目 (CXTDX201601020)

Attribute-Aware Task Allocation and Privacy-Preserving Coordination Mechanism for MCS

YANG Peng1,2 WU Qiming1,2   

  1. 1. School of Communication and Information Engineering∥ Key Laboratory of Ubiquitous Sensing and Networking in Chongqing,Chongqing University of Posts and Telecommunications,Chongqing 400065,China; 2. West Institute of CAICT
    of MIIT,Chongqing 401336,China
  • Received:2019-10-15 Revised:2020-02-01 Online:2020-08-25 Published:2020-08-01
  • Contact: 杨鹏(1980-),男,高级工程师,主要从事下一代移动通信技术研究。 E-mail:yangpeng@caict. ac. cn
  • About author:杨鹏(1980-),男,高级工程师,主要从事下一代移动通信技术研究。
  • Supported by:
    Supported by the National Natural Science Foundation of China (61771082,61871062) and the Program for Innovation Team Building at the Institutions of Higher Education in Chongqing (CXTDX201601020)

摘要: 针对移动群智感知网络中感知的任务分配以及保护感知用户的隐私信息问题,提出了一种基于用户属性感知的任务分配与隐私保护协同机制。首先,根据感知用户固有属性以及历史任务参与记录,挖掘用户对任务的不同倾向、意愿和访问等来量化出用户的静态属性和社会属性; 然后,将用户属性作为输入,使用 BP 神经网络对用户服务能力进行分析,实现任务与用户的优化分配; 最后,感知用户生成假名参与感知任务,结合环签名对用户属性生成随机数进行属性加密,确保感知用户在隐私安全的前提下,提升平台感知数据的准确程度。仿真实验结果表明,文中所提出的策略能够有效地选择出感知用户,验证了用户上传数据的可用性,保护了用户的身份安全。

关键词: 群智感知, 任务分配, 隐私保护, 属性签名

Abstract: Aiming at the problems of sensing task allocation and the protection of private information of the sensing user in mobile crowd sensing network,a collaborative mechanism of task allocation and privacy protection based on user attribute awareness was proposed. Firstly,according to the inherent attributes of the sensing user and the his-torical task participation record,the user's different tendencies,wishes and access to the task were mined and taken as the indexes to quantify the user's static attributes and social attributes. Then,the user attributes were considered as input,and the BP neural network was used to analyze user service capability,so as to realize the optimal alloca-tion of tasks and users. Finally,the sensing user generated pseudonyms to participate in the sensing task,and the random number generated by user attributes was encrypted based on the ring signature. Under the premise of ensu-ring the privacy of the perceived users,the accuracy of the platform's perceived data was improved. The simulation experiment results show that the proposed strategy can effectively select the sensing users,validate the availability of the user's uploaded data,and protect the user's identity security.

Key words: mobile crowd sensing, task allocation, privacy-preserving, attribute encryption