Blockchain-Enabled Defence Strategy for Attacks Prevention and Detection in IoT Ecosystem
Vinay Maurya, Vinay Rishiwal, Dharm Singh Jat, Preeti Yadav, Mano Yadav, Arpit Jain, Brijesh Kumar Chaurasia · 2024
The Internet of Things networks (IoT-N) enable devices to communicate via diverse methods and protocols. However, they also present significant security hazards. Yet, they also pose substantial security risks. Addressing these risks is quite challenging as traditional security measures, like software and firewalls, often need to catch up to attain the specific requirements of IoT devices. The proposed work presents a hybrid intrusion detection system (HIDS) incorporating blockchain and machine learning technologies to register IoT devices, detect and prevent attacks, and verify nodes through smart contracts. The proposed approach enables rapid and efficient detection of malicious nodes to enhance security measures. To evaluate the performance of the BC-based HIDS in safeguarding IoT networks against threats, we considered the performance metrics, viz. threshold, packet, and regular attacks. The results demonstrate the proposed HIDS's efficacy and outstrips with traditional intrusion detection approaches that offer a more robust security framework. Furthermore, BC plays a vital role in storing corrupted data in IoT networks and enhancing security. The performance of the proposed HIDS signifies that uniting ML and BC is promising to protect IoT networks from malicious security threats.