Anomaly dependent intrusion detection framework for industrial internet of things
Laboni Sarkar, Ranjan Kumar Mondal · 2024
The Internet of Things (IoT) represents an expansive network of interconnected smart devices, continuously growing in size and complexity. This network facilitates the exchange of information among devices, impacting various services and the daily activities of individuals. The efficacy and reliability of IoT are foundational to its integration into daily life, necessitating robust security measures to safeguard its operations. These measures are critical for ensuring secure communications, preventing unauthorized access or disruptions, and maintaining data confidentiality within sensor nodes through encryption. Consequently, there is a pressing need to enhance IoT network security to counteract potential vulnerabilities susceptible to exploitation by malicious entities. Despite the implementation of sophisticated encryption algorithms and security protocols, IoT networks remain vulnerable to cyber threats. Therefore, this paper introduces a Lightweight Intrusion Detection System designed to identify and mitigate specific cyber threats, notably the Hello Flood and Sybil attacks, within IoT networks.