Jing Bai;Jinsong Gui;Neal N. Xiong;Anfeng Liu;Jie Wu
{"title":"L3P-DLI: A Lightweight Positioning-Privacy Protection Scheme With Double-Layer Incentives for Wireless Crowd Sensing Systems","authors":"Jing Bai;Jinsong Gui;Neal N. Xiong;Anfeng Liu;Jie Wu","doi":"10.1109/JSAC.2024.3414580","DOIUrl":null,"url":null,"abstract":"Mobile Crowd Sensing (MCS), as a promising sensing paradigm, significantly relies on wireless communication networks and widely distributed mobile workers to capture data from the surroundings. However, the positioning-dependent nature of most MCS tasks often requires workers to embed their positionings in reports, which may result in privacy leakage and a decline in their participation enthusiasm. Considering workers’ diverse perceptions of positioning privacy, in this paper we propose the Lightweight Positioning-Privacy Protection Scheme with Double-Layer Incentives (L3P-DLI) to meet their personalized privacy requirements in an efficient and low-cost way while stimulating their participation. To the best of our knowledge, this scheme is the first attempt to employ proxy forwarding to protect workers’ sensitive positionings while ensuring high-quality sensing results. Moreover, our double-layer incentivizing mechanism is elaborately designed to motivate workers to actively participate or serve as proxies. Specifically, the bidirectional auction between data collectors and proxies can safeguard the security of data collectors, and compensate for the potential privacy leakage cost of proxies helping to forward data. Additionally, the reverse auction mechanism enables the platform to reward recruited workers to compensate for their various costs. Extensive experiments conducted on real-world datasets validate that L3P-DLI effectively preserves workers’ positioning privacy while maximizing their income to encourage participation.","PeriodicalId":73294,"journal":{"name":"IEEE journal on selected areas in communications : a publication of the IEEE Communications Society","volume":"42 10","pages":"2938-2953"},"PeriodicalIF":0.0000,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE journal on selected areas in communications : a publication of the IEEE Communications Society","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10557709/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Mobile Crowd Sensing (MCS), as a promising sensing paradigm, significantly relies on wireless communication networks and widely distributed mobile workers to capture data from the surroundings. However, the positioning-dependent nature of most MCS tasks often requires workers to embed their positionings in reports, which may result in privacy leakage and a decline in their participation enthusiasm. Considering workers’ diverse perceptions of positioning privacy, in this paper we propose the Lightweight Positioning-Privacy Protection Scheme with Double-Layer Incentives (L3P-DLI) to meet their personalized privacy requirements in an efficient and low-cost way while stimulating their participation. To the best of our knowledge, this scheme is the first attempt to employ proxy forwarding to protect workers’ sensitive positionings while ensuring high-quality sensing results. Moreover, our double-layer incentivizing mechanism is elaborately designed to motivate workers to actively participate or serve as proxies. Specifically, the bidirectional auction between data collectors and proxies can safeguard the security of data collectors, and compensate for the potential privacy leakage cost of proxies helping to forward data. Additionally, the reverse auction mechanism enables the platform to reward recruited workers to compensate for their various costs. Extensive experiments conducted on real-world datasets validate that L3P-DLI effectively preserves workers’ positioning privacy while maximizing their income to encourage participation.