Maximizing privacy and security of collaborative indoor positioning using zero-knowledge proofs

The increasing popularity of wearable-based Collaborative Indoor Positioning Systems (CIPSs) has led to the development new methods for improving positioning accuracy. However, these systems often rely on protocols, such as iBeacon, that lack sufficient privacy protection. In addition, they depend centralized entities authentication and verification processes. To address limitations existing this paper presents a groundbreaking contribution field CIPSs. We propose decentralized Attribute-based Authentication (ABA) protocol offers superior levels protection, untraceability, unlinkability user actions. Unlike protocols entities, our approach leverages mechanisms verification, ensuring location data exchange. Through extensive experimentation across multiple platforms, results demonstrate practicality feasibility proposed real-world deployment. Overall, work opens up avenues secure privacy-preserving CIPSs, with potential implications rapidly growing Internet Things (IoT) applications.