An Optimized Intrusion Detection Scheme for Industrial Control Systems in IIOT
Li Ma, Zhaoxiong Bu, Wenyin Yang, Jihui Li, Zhongrong Zeng, Baoyao Yang · 2024
As the Industrial Internet of Things (IIoT) expands, security vulnerabilities in Industrial Control Systems (ICS) have escalated, challenging traditional Intrusion Detection Systems (IDS). This study introduces FiPCAi, a new feature selection method combining Fisher-Score, Incremental PCA, and ChatGPT, to enhance IDS efficiency in multi-source IIoT environments. We also present the CMA-BiLSTM model, which integrates CNN with a multi-head attention mechanism in a BiLSTM framework, demonstrating superior detection capabilities on datasets such as CIC-IDS2017 and CSE-CIC-IDS2018, with noted accuracies above 98%. A DANN-based transfer learning experiment on the WUSTL-IIOT-2021 dataset further confirmed the model’s robust generalization, achieving $\mathbf{9 8. 6 \%}$ accuracy.