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Toward Privacy Preserving and Collusion Resistance in a Location Proof Updating System
| Venue: | IEEE TRANSACTIONS ON MOBILE COMPUTING |
| Citations: | 6 - 0 self |
BibTeX
@MISC{Zhu_towardprivacy,
author = {Zhichao Zhu and Guohong Cao},
title = {Toward Privacy Preserving and Collusion Resistance in a Location Proof Updating System },
year = {}
}
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Abstract
Today’s location-sensitive service relies on user’s mobile device to determine the current location. This allows malicious users to access a restricted resource or provide bogus alibis by cheating on their locations. To address this issue, we propose A Privacy-Preserving LocAtion proof Updating System (APPLAUS) in which co-located Bluetooth enabled mobile devices mutually generate location proofs and send updates to a location proof server. Periodically changed pseudonyms are used by the mobile devices to protect source location privacy from each other, and from the untrusted location proof server. We also develop user-centric location privacy model in which individual users evaluate their location privacy levels and decide whether and when to accept the location proof requests. In order to defend against colluding attacks, we also present betweenness ranking based and correlation clustering based approaches for outlier detection. APPLAUS can be implemented with existing network infrastructure, and can be easily deployed in Bluetooth enabled mobile devices with little computation or power cost. Extensive experimental results show that APPLAUS can effectively provide location proofs, significantly preserve the source location privacy, and effectively detect colluding attacks.
Keyphrases
final publication towards privacy preserving collusion resistance ieee transaction mobile computing future issue location proof mobile device source location privacy privacy-preserving location proof location proof server network infrastructure malicious user co-located bluetooth index term location untrusted location proof server present betweenness user mobile device bogus alibi location privacy individual user correlation clustering location privacy level user-centric location privacy model location-sensitive service relies little computation extensive experimental result location proof request power cost current location abstract today
