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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Main Authors: Yi, Xun, Lam, Kwok-Yan, Bertino, Elisa, Rao, Fang-Yu
Other Authors: School of Computer Science and Engineering
Format: Conference or Workshop Item
Language:English
Published: 2020
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Online Access:https://hdl.handle.net/10356/138424
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Institution: Nanyang Technological University
Language: English
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spelling 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
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic Engineering::Computer science and engineering
Mobile Crowd Sensing
Location Privacy Protection
spellingShingle 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
description 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.
author2 School of Computer Science and Engineering
author_facet School of Computer Science and Engineering
Yi, Xun
Lam, Kwok-Yan
Bertino, Elisa
Rao, Fang-Yu
format 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