Location privacy-preserving mobile crowd sensing with anonymous reputation
In this paper, we give a location privacy-preserving solution for the mobile crowd sensing (MCS) system. The solution makes use of the blind signature technique for anonymous authentication and allows a mobile user to participate in the MCS for certain times set in the registration. Furthermore, we...
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sg-ntu-dr.10356-1384242020-09-26T22:03:59Z Location privacy-preserving mobile crowd sensing with anonymous reputation Yi, Xun Lam, Kwok-Yan Bertino, Elisa Rao, Fang-Yu School of Computer Science and Engineering 24th European Symposium on Research in Computer Security This research/project is supported by the National Research Foundation, Singapore under its Strategic Capability Research Centres Funding Initiative. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not reflect the views of National Research Foundation, Singapore. Engineering::Computer science and engineering Mobile Crowd Sensing Location Privacy Protection In this paper, we give a location privacy-preserving solution for the mobile crowd sensing (MCS) system. The solution makes use of the blind signature technique for anonymous authentication and allows a mobile user to participate in the MCS for certain times set in the registration. Furthermore, we introduce a concept of anonymous reputation for mobile users on the basis of the blind signature technique as well. An anonymous reputation can be referred by the MCS platform when assigning tasks to a mobile user and can be upgraded or downgraded by the MCS platform, depending on the quality of reports submitted by the mobile user. For the security analysis, we provide security proofs for our solution on the basis of our formal definitions for anonymity, unlinkability and unforgeability for MCS. The performance analysis and experiments have shown that our solution is more efficient than existing solutions for MCS based on the blind signature technique. NRF (Natl Research Foundation, S’pore) Accepted version 2020-05-06T02:24:08Z 2020-05-06T02:24:08Z 2019 Conference Paper Yi, X., Lam, K.-Y., Bertino, E., & Rao, F.-Y. (2019). Location privacy-preserving mobile crowd sensing with anonymous reputation. Computer Security – ESORICS 2019, 387-411. doi:10.1007/978-3-030-29962-0_19 9783030299613 https://hdl.handle.net/10356/138424 10.1007/978-3-030-29962-0_19 2-s2.0-85075624696 387 411 en © 2019 Springer Nature Switzerland AG. All rights reserved. This paper was published in Computer Security – ESORICS 2019 and is made available with permission of Springer Nature Switzerland AG. application/pdf |
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Engineering::Computer science and engineering Mobile Crowd Sensing Location Privacy Protection Yi, Xun Lam, Kwok-Yan Bertino, Elisa Rao, Fang-Yu Location privacy-preserving mobile crowd sensing with anonymous reputation |
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In this paper, we give a location privacy-preserving solution for the mobile crowd sensing (MCS) system. The solution makes use of the blind signature technique for anonymous authentication and allows a mobile user to participate in the MCS for certain times set in the registration. Furthermore, we introduce a concept of anonymous reputation for mobile users on the basis of the blind signature technique as well. An anonymous reputation can be referred by the MCS platform when assigning tasks to a mobile user and can be upgraded or downgraded by the MCS platform, depending on the quality of reports submitted by the mobile user. For the security analysis, we provide security proofs for our solution on the basis of our formal definitions for anonymity, unlinkability and unforgeability for MCS. The performance analysis and experiments have shown that our solution is more efficient than existing solutions for MCS based on the blind signature technique. |
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School of Computer Science and Engineering |
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School of Computer Science and Engineering Yi, Xun Lam, Kwok-Yan Bertino, Elisa Rao, Fang-Yu |
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Conference or Workshop Item |
author |
Yi, Xun Lam, Kwok-Yan Bertino, Elisa Rao, Fang-Yu |
author_sort |
Yi, Xun |
title |
Location privacy-preserving mobile crowd sensing with anonymous reputation |
title_short |
Location privacy-preserving mobile crowd sensing with anonymous reputation |
title_full |
Location privacy-preserving mobile crowd sensing with anonymous reputation |
title_fullStr |
Location privacy-preserving mobile crowd sensing with anonymous reputation |
title_full_unstemmed |
Location privacy-preserving mobile crowd sensing with anonymous reputation |
title_sort |
location privacy-preserving mobile crowd sensing with anonymous reputation |
publishDate |
2020 |
url |
https://hdl.handle.net/10356/138424 |
_version_ |
1681057326548647936 |