Deep transfer learning for intrusion detection in industrial control networks: A comprehensive review

arXiv:2304.10550v2 Announce Type: replace-cross
Abstract: Globally, the external internet is increasingly being connected to industrial control systems. As a result, there is an immediate need to protect these networks from a variety of threats. The key infrastructure of industrial activity can be protected from harm using an intrusion detection system (IDS), a preventive mechanism that seeks to recognize new kinds of dangerous threats and hostile activities. This review examines the most recent artificial-intelligence techniques that are used to create IDSs …

abstract arxiv control control systems cs.ai cs.cr cs.lg cs.ni cs.sy detection eess.sy harm industrial industrial control infrastructure internet key networks protect review systems the key threats transfer transfer learning type