EPoLBFT: A Blockchain Consensus Algorithm for Enhancing Privacy, Invulnerability and Trust in IoT System

The rapid growth of Internet of Things (IoT) systems has introduced significant challenges related to privacy, trust, scalability, and attack resilience, particularly in resource-constrained and location-sensitive environments. Existing blockchain consensus mechanisms provide decentralised trust, but they often suffer from high communication overhead, weak physical-context awareness, and limited privacy protection when deployed in large-scale IoT networks. This paper proposes Elastic Proof-of-Location Byzantine Fault Tolerance (EPoLBFT), a privacy-preserving and location-aware blockchain consensus framework for IoT systems. The proposed design enables IoT nodes to prove regional eligibility without revealing exact coordinates while restricting consensus participation to trusted and geographically verified validators. EPoLBFT is evaluated using the Blockchain IoT Consensus Algorithm (BICA) simulator under normal, high-load, Byzantine, Sybil, location-spoofing, and denial-of-service scenarios. The evaluation considers latency, throughput, communication overhead, energy consumption, and attack resilience. The results show that EPoLBFT reduces communication overhead and improves consensus efficiency compared with conventional PBFT-based approaches while strengthening resilience against location-based and identity-based attacks. The study also discusses the privacy–latency trade-off introduced by zk-PoL, the assumptions related to trusted location anchors, and the limitations of simulation-based evaluation.