A hybrid intrusion detection system in industry 4.0 based on ISA95 standard

Today with the emergence of an industrial information system (IIS) in industry of the future that includes the connection between all trades, applications and the converged technologies between Information Technology (IT) and Operational Technology (OT), cybersecurity has become an emergency. Industrial IDS are no longer enough to counter cyberattacks because of their natures, which is usually misuse and are unable to detect attacks that target the application layer of Open Systems Interconnection model (OSI). Therefore, cybersecurity in industrial systems adopts known IT security solutions, such as Intrusion Detection System (IDS) which has to be modified, completed and adapted to work in industrial field. We propose to deepen this approach by developing an adapted IDS to monitor industrial systems against illegitimate access and detect abnormal activities. For this purpose, we expose in this paper our efficient hybrid intrusion detection solution based on International Society of Automation 95 standard (ISA95 standard) and Neural network. Our research work is focused on Manufacturing Executive System (MES) which represents the central and main element in the industry