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Anomaly Detection of Security Threats to Cyber-Physical Systems: A Study

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17th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2022) (SOCO 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 531))

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Abstract

As the presence of Cyber-Physical Systems (CPS) becomes ubiquitous throughout all facets of modern society, malicious attacks by hostile actors have increased exponentially in recent years. Attacks on critical national infrastructure (CNI) such as oil pipelines or electrical power grids have become commonplace, as increased connectivity to the public internet increases the attack surface of CPS. This paper presents a study of the current academic literature describing the state of the art for anomaly detection of security threats to Cyber-Physical Systems, with a focus on life safety issues for industrial control networks (ICS), with the goal of improving the accuracy of anomaly detection. As a new contribution, this paper also identifies outstanding challenges 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. University of León, León, Spain

    Hilde Pérez García

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

    Francisco Javier Martinez-de-Pison

  4. Inteligencia Artificial, University of Oviedo, A Coruña, La Coruña, Spain

    José Ramón Villar Flecha

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

    Alicia Troncoso Lora

  6. University of Oviedo, Oviedo, Spain

    Enrique A. de la Cal

  7. Department of Civil Engineering, University of Burgos, Burgos, Spain

    Álvaro Herrero

  8. School of engineering, Pablo Olavide University, Seville, Spain

    Francisco Martínez Álvarez

  9. DIGIP, University of Bergamo, Dalmine, Bergamo, Italy

    Giuseppe Psaila

  10. Department of Industrial Engineering, University of A Coruña, Ferrol, Spain

    Héctor Quintián

  11. Department of Computing Science, University of Salamanca, Salamanca, Spain

    Emilio S. Corchado Rodriguez

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Jeffrey, N., Tan, Q., Villar, J.R. (2023). Anomaly Detection of Security Threats to Cyber-Physical Systems: A Study. In: García Bringas, P., et al. 17th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2022). SOCO 2022. Lecture Notes in Networks and Systems, vol 531. Springer, Cham. https://doi.org/10.1007/978-3-031-18050-7_1

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