Scalable and Secure Architecture for Distributed IoT Systems
This addresses security and scalability challenges for IoT systems, though it appears incremental as it builds on existing blockchain and AI methods.
The paper tackles security vulnerabilities in centralized IoT systems by proposing a novel architecture combining permissioned blockchain and AI-based anomaly detection at gateways, achieving high performance against cyber-attacks in simulations and practical implementation.
Internet-of-things (IoT) is perpetually revolutionizing our daily life and rapidly transforming physical objects into an ubiquitous connected ecosystem. Due to their massive deployment and moderate security levels, those devices face a lot of security, management, and control challenges. Their classical centralized architecture is still cloaking vulnerabilities and anomalies that can be exploited by hackers for spying, eavesdropping, and taking control of the network. In this paper, we propose to improve the IoT architecture with additional security features using Artificial Intelligence (AI) and blockchain technology. We propose a novel architecture based on permissioned blockchain technology in order to build a scalable and decentralized end-to-end secure IoT system. Furthermore, we enhance the IoT system security with an AI-component at the gateway level to detect and classify suspected activities, malware, and cyber-attacks using machine learning techniques. Simulations and practical implementation show that the proposed architecture delivers high performance against cyber-attacks.