Skip to Main content Skip to Navigation
Preprints, Working Papers, ...

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

Salwa Alem 1 David Espes 2 Eric Martin 3 Laurent Nana 1 Florent de Lamotte 4
2 Lab-STICC_UBO_CID_SFIIS
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance
3 Lab-STICC_UBS_CACS_MOCS
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance
Abstract : 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.
Complete list of metadatas

Cited literature [20 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-02506109
Contributor : Salwa Alem <>
Submitted on : Thursday, October 8, 2020 - 5:19:14 PM
Last modification on : Sunday, October 11, 2020 - 3:04:51 AM

File

Hybrid-IDS-Based-on-ISA95--.pd...
Files produced by the author(s)

Identifiers

  • HAL Id : hal-02506109, version 2

Citation

Salwa Alem, David Espes, Eric Martin, Laurent Nana, Florent de Lamotte. A hybrid intrusion detection system in industry 4.0 based on ISA95 standard. 2020. ⟨hal-02506109v2⟩

Share

Metrics

Record views

16

Files downloads

35