Distributed Ledgers for Enhanced Machine-to-Machine Trust in Smart Cities

Abstract

Incorporating smart technology into critical infras-tructure (CI) and smart cities promises substantial efficiency improvements as networks of machines communicate and make rapid decisions autonomously. Yet the promise of greater effi-ciency that such cyber-physical systems (CPS) bring is tempered by increased fragility unless machine-to-machine (M2M) trust is enhanced, particularly in Internet of Things (IoT) networks. This work makes two contributions toward improving M2M trust. First, it proposes a multifaceted trust framework comprised of identity verification, experience, context, and recommendation scores to enable high-integrity M2M interactions. Second, this trust framework is implemented via an IoT-friendly distributed ledger on a physical testbed, where it is shown to identify and mitigate errors due to a compromised system component. This implementation mirrors real-world IoT systems in which resource-constrained endpoint devices pose trust score compu-tation challenges and the number of devices raises scalability obstacles for information sharing among nodes.