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

Faheem Zafar, Abid Khan, Saif Ur Rehman Malik, Mansoor Ahmed, Carsten Maple*, Adeel Anjum

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (SciVal)
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Abstract

Smart devices have accentuated the importance of geolocation information. Geolocation identification using smart devices has paved the path for incentive-based location-based services (LBS). However, a user’s full control over a smart device can allow tampering of the location proof. Witness-oriented location proof systems (LPS) have emerged to resist the generation of false proofs and mitigate collusion attacks. However, witness-oriented LPS are still susceptible to three-way collusion attacks (involving the user, location authority, and the witness). To overcome the threat of three-way collusion in existing schemes, we introduce a decentralized consensus protocol called MobChain in this paper. In this scheme the selection of a witness and location authority is achieved through a distributed consensus of nodes in an underlying P2P network that establishes a private blockchain. The persistent provenance data over the blockchain provides strong security guarantees; as a result, the forging and manipulation of location becomes impractical. MobChain provides secure location provenance architecture, relying on decentralized decision making for the selection of participants of the protocol thereby addressing the three-way collusion problem. Our prototype implementation and comparison with the state-of-the-art solutions show that MobChain is computationally efficient and highly available while improving the security of LPS.
Original languageEnglish
Article number5096
Number of pages32
JournalSensors
Volume21
Issue number15
Early online date28 Jul 2021
DOIs
Publication statusPublished - 28 Jul 2021

Keywords

  • Blockchain
  • Localization
  • Location proof
  • Location provenance
  • Location-based services (LBS)
  • Humans
  • Consensus

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