Deep Learning Approaches for Intrusion Detection in IIoT Networks – Opportunities and Future Directions

In recent years, the Industrial Internet of things (IIoT) is a fastest advancing innovative technology with poten-tial to digitize and interconnect many industries for huge business opportunities development global GDP. IIoT used in diverse range such as manufacturing, logistics, transportation, oil gas, mining metals, energy utilities aviation. Although provides promising different industrial applications, they are prone cyberattacks demands higher security require-ments. The enormous number sensors present network generates large amount data has attracted attention cybercriminals across globe. intrusion detection system (IDS) that monitors traffic detects behaviour considered one key solution securing application from attacks. Recently, machine deep learning techniques have proved mitigate multiple threats enhance performance detection. this paper, we survey learning-based IDS technique IIoT. main objective research provide various methods, datasets comwparative analysis. Finally, aims identify limitations challenges existing studies, solutions future directions.