Blockchain localization spoofing detection based on Fuzzy AHP in IoT systems

Location spoofing detection is an important part of location proof schemes in IoT systems. It is important for location systems to accurately evaluate the credibility of location data uploaded by users. Differ with the works employing physical layer features such as signal strength or channel state information, we focus on laying the foundation for solutions aiming to build the location spoofing detection functions in the blockchain based IoT systems. More specifically,an IoT system is established at the node level and the moving-track level for the evaluation of the credibility of location proof with the characteristics of the blockchain positioning system. A multi-layer fuzzy Analytic Hierarchy Process (AHP) evaluation method is considered for the detection of location spoofing in blockchains. The simulation results show that the proposed scheme is practical, and can provide a reference for the credibility evaluation of location proof.

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

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.

Dynamic Membership Management in Anonymous and Deniable Distance Bounding

For secure location proof in many applications, distance bounding protocols are considered as one of the useful tools that can be used in practice. In distance bounding protocols, a prover and a verifier can measure the distance between them by performing an interactive protocol. In general, the verifier is regarded as an honest service provider, and thus, an adversarial verifier is not considered for security analysis. However, we cannot ignore the possibility of the corruption of the verifier, which can spoil the prover’s privacy. To handle the security problem, a prover-anonymous and deniable distance bounding protocol is proposed, which can guarantee the privacy of the prover even though the verifier is corrupted. In this paper, we review the prover-anonymous and deniable distance bounding protocol in terms of the membership management, and we show that the communication overhead in the protocol for each membership change is O(n) where n is the number of users. Then, we propose an improved membership management technique, which can efficiently support membership change in terms of the communication overhead. The improved technique requires O(1) for each membership change instead of O(n), as in the existing protocol.

Location Proof Systems for Smart Internet of Things: Requirements, Taxonomy, and Comparative Analysis

In the current hyper-connected, data-driven era, smart devices are providing access to geolocation information, enabling a paradigm shift in diverse domains. Location proof systems utilize smart devices to provide witnessed proof of location to enable secure location-based services (LBS). Applications of location proof systems include safety, asset management and operations monitoring in health care, supply chain tracking, and Internet-of-Things (IoT)-based location intelligence in businesses. In this paper, we investigate the state of the art in location proof systems, examining design challenges and implementation considerations for application in the real world. To frame the analysis, we have developed a taxonomy of location proof systems and performed a comparative analysis over the common attributes, highlighting their strength and weaknesses. Furthermore, we have identified future trends for this increasingly important area of investigation and development.