Personalized Location Privacy Trading in Double Auction for Mobile Crowdsensing

被引:13
作者
Wang, Jiandong [1 ]
Liu, Hao [1 ]
Dong, Xuewen [1 ]
Shen, Yulong [1 ]
Zhu, Xinghui [1 ]
Wang, Bin [2 ]
Li, Feng
机构
[1] Xidian Univ, Sch Comp Sci & Technol, Xian 710071, Peoples R China
[2] Zhejiang Key Lab Multidimens Percept Technol Appli, Hangzhou 310053, Peoples R China
基金
中国国家自然科学基金;
关键词
Privacy; Task analysis; Sensors; Crowdsensing; Internet of Things; Data privacy; Roads; Double auction; location privacy; mobile crowdsensing; privacy budget; MANAGEMENT; MECHANISM; SYSTEM;
D O I
10.1109/JIOT.2022.3233052
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Mobile crowdsensing systems (MCSs) are widely used in data collection due to their flexible deployment and comprehensive coverage in many IoT scenarios (e.g., road condition monitoring). Recently, the difference between workers' perception on location privacy has drawn researchers' attention. The only privacy trading mechanism in MCSs has been designed, however, in a single auction and single-minded way. Realizing task requesters' competition requirement and workers' task preference variance, in this article, we are the first to propose a double MCS auction mechanism with a personalized location privacy incentive. Specifically, this article introduces the concept of privacy budget, allowing workers to decide how much location information to disclose to the platform to realize personalized location privacy protection. Besides, considering the heterogeneity of sensing tasks and the diversity of task selection, each worker is allowed to offer several bids for interested tasks and to perform a subset of tasks in a bid if wins. In addition, our auction mechanism enables the platform to select winning requesters and workers and achieve ideal sensing service accuracy. Extensive theoretical analysis and experiment results validate that the proposed mechanism satisfies budget balance, individual rationality, and 2-D-truthfulness.
引用
收藏
页码:8971 / 8983
页数:13
相关论文
共 32 条
  • [1] Surface monitoring of road pavements using mobile crowdsensing technology
    Abbondati, Francesco
    Biancardo, Salvatore Antonio
    Veropalumbo, Rosa
    Dell'Acqua, Gianluca
    [J]. MEASUREMENT, 2021, 171
  • [2] A Survey on Mobile Crowd-Sensing and Its Applications in the IoT Era
    Abualsaud, Khalid
    Elfouly, Tarek M.
    Khattab, Tamer
    Yaacoub, Elias
    Ismail, Loay Sabry
    Ahmed, Mohamed Hossam
    Guizani, Mohsen
    [J]. IEEE ACCESS, 2019, 7 : 3855 - 3881
  • [3] Andres M.E., 2013, P 2013 ACM SIGSAC C, P901
  • [4] Capponi A, 2019, IEEE COMMUN SURV TUT, V21, P2419, DOI [10.1109/COMST.2019.2914030, 10.1109/isscs.2019.8801767]
  • [5] Ding X, 2021, COMPUT ELECTR ENG, V97
  • [6] Optimizing Task Location Privacy in Mobile Crowdsensing Systems
    Dong, Xuewen
    Zhang, Wen
    Zhang, Yushu
    You, Zhichao
    Gao, Sheng
    Shen, Yulong
    Wang, Chao
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2022, 18 (04) : 2762 - 2772
  • [7] Optimal Mobile Crowdsensing Incentive Under Sensing Inaccuracy
    Dong, Xuewen
    You, Zhichao
    Luan, Tom H.
    Yao, Qingsong
    Shen, Yulong
    Ma, Jianfeng
    [J]. IEEE INTERNET OF THINGS JOURNAL, 2021, 8 (10): : 8032 - 8043
  • [8] Towards a Practical Crowdsensing System for Road Surface Conditions Monitoring
    El-Wakeel, Amr S.
    Li, Jin
    Noureldin, Aboelmagd
    Hassanein, Hossam S.
    Zorba, Nizar
    [J]. IEEE INTERNET OF THINGS JOURNAL, 2018, 5 (06): : 4672 - 4685
  • [9] Differentially Private Task Allocation Algorithm Under Preference Protection
    Han, Juntao
    Cai, Shuyue
    [J]. IEEE ACCESS, 2022, 10 : 33059 - 33068
  • [10] Jin HM, 2017, IEEE INFOCOM SER