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MobChain: Three-Way Collusion Resistance in Witness-Oriented Location\n Proof Systems Using Distributed Consensus

  • arXiv (Cornell University)
  • Cornell University
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Smart devices have accentuated the importance of geolocation information.\nGeolocation identification using smart devices has paved the path for\nincentive-based location-based services (LBS). A location proof is a digital\ncertificate of the geographical location of a user, which can be used to access\nvarious LBS. However, a user full control over a device allows the tampering of\nlocation proof. Initially, to resist false proofs, two-party trusted\ncentralized location proof systems (LPS) were introduced to aid the users in\ngenerating secure location proofs mutually. However, two-party protocols\nsuffered from the collusion attacks by the participants of the protocol.\nConsequently, many witness-oriented LPS have emerged to mitigate collusion\nattacks in two-party protocols. However, witness-oriented LPS presented the\npossibility of three-way collusion attacks (involving the user, location\nauthority, and the witness). The three-way collusion attacks are inevitable in\nall existing witness-oriented schemes. To mitigate the inability to resist\nthree-way collusion of existing schemes, in this paper, we introduce a\ndecentralized consensus protocol called as MobChain, where the selection of a\nwitness and location authority is achieved through a distributed consensus of\nnodes in an underlying P2P network of a private blockchain. The persistent\nprovenance data over the blockchain provides strong security guarantees, as a\nresult, the forging and manipulation become impractical. MobChain provides\nsecure location provenance architecture, relying on decentralized decision\nmaking for the selection of participants of the protocol to resist three-way\ncollusion problem. Our prototype implementation and comparison with the\nstate-of-the-art solutions show that MobChain is computationally efficient,\nhighly available while improving the security of LPS.\n

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Publication details

DOI
10.48550/arxiv.2011.08538
OpenAlex
W4287595227
Document type
preprint
Language
EN
Source
arXiv (Cornell University)
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