Blockchain Based Secure Threat Detection Model for Industrial IoT Applications

Abstract

Securing data in the Industrial Internet of Things (IIoT) is critical due to the growing complexity and scale of industrial networks. Integrating Ethereum-based blockchain technology offers a promising solution by leveraging distributed ledgers to enhance the transparency, immutability, and security of IIoT systems. This study aims to enhance threat detection and data protection in IIoT environments through blockchain integration. To achieve this, the proposed approach incorporates Dynamic Threat Landscape (DTL)-based Intrusion Detection Systems (IDS) for real-time attack modelling, enabling systems to adapt to evolving threats. However, integrating blockchain with IIoT also presents challenges, including ensuring low latency for real-time processing, scalability to manage large volumes of sensor data, and maintaining robust cybersecurity while preserving data privacy and integrity. Addressing these concerns is essential for the effective deployment of blockchain-enabled threat detection in IIoT networks.