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Intrusion Detection and Prevention in Industrial Internet of Things: A Study

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International Joint Conference 16th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2023) 14th International Conference on EUropean Transnational Education (ICEUTE 2023) (CISIS 2023, ICEUTE 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 748))

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Abstract

The Industrial Internet of Things (IIoT) brings the ubiquitous connectivity of the Internet of Things (IoT) to industrial processes, optimizing manufacturing and civil infrastructures with assorted “smart” technologies. This ubiquitous connectivity to industrial processes has increased the attack surface available to threat actors, with increasingly frequent cyber attacks on physical infrastructure resulting in significant economic and life safety consequences, due to service interruptions in power grids, oil distribution pipelines, etc. The difference between IoT and IIoT is largely one of degree, with the consequence of service interruptions to IoT (ie home automation) typically limited to mild inconvenience, while interruptions to IIoT environments (ie power grids) have more significant economic and life safety consequences. The field of Intrusion Detection Systems / Intrusion Prevention Systems (IDS/IPS) has traditionally focused on cyber components rather than physical components, which has resulted in threat detection capabilities in IIoT environments lagging behind their non-industrial counterparts, leading to increasingly frequent attacks by threat actors against critical infrastructure. This paper reviews the current state of IDS/IPS capabilities in industrial environments and compares the maturity and effectiveness to the more established IDS/IPS capabilities of non-industrial Information Technology (IT) networks. As a new contribution, this paper also identifies gaps in the existing research in the field, and maps selected challenges to potential solutions and/or opportunities for further research.

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Acknowledgement

This research has been funded by the SUDOE Interreg Program -grant INUNDATIO-, by the Spanish Ministry of Economics and Industry, grant PID2020-112726RB-I00, by the Spanish Research Agency (AEI, Spain) under grant agreement RED2018–102312-T (IA-Biomed), and by the Ministry of Science and Innovation under CERVERA Excellence Network project CER-20211003 (IBERUS) and Missions Science and Innovation project MIG-20211008 (INMERBOT). Also, by Principado de Asturias, grant SV-PA-21-AYUD/2021/50994.

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Authors and Affiliations

  1. University of Oviedo, Oviedo, Spain

    Nicholas Jeffrey & José R. Villar

  2. Athabasca University, Athabasca, Canada

    Qing Tan

Authors
  1. Nicholas Jeffrey
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  2. Qing Tan
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  3. José R. Villar
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Corresponding author

Correspondence to Nicholas Jeffrey .

Editor information

Editors and Affiliations

  1. Faculty of Engineering, University of Deusto, Bilbao, Spain

    Pablo García Bringas

  2. School of Industrial, Computer and Aerospace Engineering, University of Leon, León, Spain

    Hilde Pérez García

  3. Department of Mechanical Engineering, University of La Rioja, Logroño, Spain

    Francisco Javier Martínez de Pisón

  4. Data Science and Big Data Lab, Pablo de Olavide University, Seville, Spain

    Francisco Martínez Álvarez

  5. Data Science and Big Data Lab, Pablo de Olavide University, Seville, Spain

    Alicia Troncoso Lora

  6. Applied Computational Intelligence, University of Burgos, Burgos, Burgos, Spain

    Álvaro Herrero

  7. Department of Industrial Engineering, University of A Coruña, A Coruña, Spain

    José Luis Calvo Rolle

  8. Department of Industrial Engineering, University of A Coruña, A Coruña, Spain

    Héctor Quintián

  9. Faculty of Science, University of Salamanca, Salamanca, Spain

    Emilio Corchado

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Jeffrey, N., Tan, Q., Villar, J.R. (2023). Intrusion Detection and Prevention in Industrial Internet of Things: A Study. In: García Bringas, P., et al. International Joint Conference 16th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2023) 14th International Conference on EUropean Transnational Education (ICEUTE 2023). CISIS ICEUTE 2023 2023. Lecture Notes in Networks and Systems, vol 748. Springer, Cham. https://doi.org/10.1007/978-3-031-42519-6_4

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