Deep Dive into IIoT Intrusion Detection Systems: A Review and Future Directions
Sushama L. Pawar, Mandar Subhash Karyakarte · 2024
The Industrial Internet of Things (IIoT) has quickly become a cutting-edge technology that can transform various sectors by digitalizing and connecting them, boosting business opportunities and global economic growth. Sectors like manufacturing, logistics, transportation, energy, and aviation are increasingly adopting IIoT. However, IIoT is vulnerable to cyber threats, requiring robust security measures. The numerous sensors in IIoT systems generate vast amounts of data, attracting cybercriminals. An Intrusion Detection System (IDS), which observe network traffic to detect unusual behavior, is crucial for securing IIoT applications. Recently, machine learning and deep learning techniques have shown potential in mitigating security threats and enhancing IDS performance. This paper reviews different deep learning-based IDS methods for IIoT, including techniques, datasets, and comparative analysis, and highlights existing limitations and future research directions.