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Practical blacklist-based anonymous authentication scheme for mobile crowd sensing

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Abstract

Mobile crowd sensing (MCS) represents one of the most promising approaches for improving life quality of individuals with sensing and computing devices. MCS is playing a more and more important role in various fields of service, such as traffic monitoring and commercial advertisement. Security and privacy of communication in MCS attract increasing attention from the academia and industry since the sensing data are usually sensitive for users. Some users worry about the leakage of their private information when they share their data to the third parties. To address this issue, in this paper, we propose a practical blacklist-based anonymous authentication scheme in which users can enjoy an anonymous environment and share their information without worrying about any information leakage. Security analysis shows that our scheme can achieve anonymity, blacklistability, nonrepudiation and unlinkability. Performance evaluation demonstrates that our scheme is more efficient in terms of computation overhead compared with the existing works.

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Acknowledgments

This work is supported by the National Natural Science Foundation of China under Grants 61472065, 61350110238, 61103207, U1233108, U1333127, and 61272525, the International Science and Technology Cooperation and Exchange Program of Sichuan Province, China under Grant 2014HH0029, China Postdoctoral Science Foundation funded project under Grant 2014M552336, and State Key Laboratory of Information Security Open Foundation under Grant 2015-MS-02.

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Authors and Affiliations

  1. School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China

    Hongwei Li, Kun Jia, Haomiao Yang & Dongxiao Liu

  2. National Key Laboratory of Science and Technology on Communication, University of Electronic Science and Technology of China, Chengdu, China

    Liang Zhou

  3. State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Sciences, Beijing, 100093, China

    Hongwei Li, Kun Jia, Haomiao Yang & Dongxiao Liu

Authors
  1. Hongwei Li
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  2. Kun Jia
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  3. Haomiao Yang
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  4. Dongxiao Liu
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  5. Liang Zhou
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Correspondence to Hongwei Li.

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Li, H., Jia, K., Yang, H. et al. Practical blacklist-based anonymous authentication scheme for mobile crowd sensing. Peer-to-Peer Netw. Appl. 9, 762–773 (2016). https://doi.org/10.1007/s12083-015-0329-z

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