IDEAS home Printed from https://ideas.repec.org/a/eee/ijocip/v42y2023ics1874548223000288.html
   My bibliography  Save this article

Software-Defined Networking approaches for intrusion response in Industrial Control Systems: A survey

Author

Listed:
  • Etxezarreta, Xabier
  • Garitano, Iñaki
  • Iturbe, Mikel
  • Zurutuza, Urko

Abstract

Industrial Control Systems (ICSs) are a key technology for life-sustainability, social development and economic progress used in a wide range of industrial solutions, including Critical Infrastructures (CIs), becoming the primary target for multiple security attacks. With the increase of personalized and sophisticated attacks, the need for new tailored ICS cybersecurity mechanisms has increased exponentially, complying with specific ICS requirements that Information Technology (IT) security systems fail to meet. In this survey, a comprehensive study of ICS intrusion response is conducted, focusing on the use of Software-Defined Networking (SDN) for the development of intrusion response strategies in ICS. With its centralized control plane, increased programmability and global view of the entire network, SDN enables the development of intrusion response solutions that provide a coordinated response to mitigate attacks. Through the survey, an analysis of ICS security requirements and the applicability of SDN is conducted, identifying the advantages and disadvantages compared to traditional networking and protocols. Furthermore, a taxonomy on intrusion response strategies is presented, where different proposals are discussed and categorized according to intrusion response strategy and deployment environment characteristics. Finally, future research directions and challenges are identified.

Suggested Citation

  • Etxezarreta, Xabier & Garitano, Iñaki & Iturbe, Mikel & Zurutuza, Urko, 2023. "Software-Defined Networking approaches for intrusion response in Industrial Control Systems: A survey," International Journal of Critical Infrastructure Protection, Elsevier, vol. 42(C).
    • Handle: RePEc:eee:ijocip:v:42:y:2023:i:c:s1874548223000288
    DOI: 10.1016/j.ijcip.2023.100615
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1874548223000288
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ijcip.2023.100615?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Umer, Muhammad Azmi & Junejo, Khurum Nazir & Jilani, Muhammad Taha & Mathur, Aditya P., 2022. "Machine learning for intrusion detection in industrial control systems: Applications, challenges, and recommendations," International Journal of Critical Infrastructure Protection, Elsevier, vol. 38(C).
    2. Miller, Thomas & Staves, Alexander & Maesschalck, Sam & Sturdee, Miriam & Green, Benjamin, 2021. "Looking back to look forward: Lessons learnt from cyber-attacks on Industrial Control Systems," International Journal of Critical Infrastructure Protection, Elsevier, vol. 35(C).
    3. Sufian Hameed & Hassan Ahmed Khan, 2018. "SDN Based Collaborative Scheme for Mitigation of DDoS Attacks," Future Internet, MDPI, vol. 10(3), pages 1-18, February.
    4. Sándor, Hunor & Genge, Béla & Szántó, Zoltán & Márton, Lőrinc & Haller, Piroska, 2019. "Cyber attack detection and mitigation: Software Defined Survivable Industrial Control Systems," International Journal of Critical Infrastructure Protection, Elsevier, vol. 25(C), pages 152-168.
    5. Barbosa, Rafael Ramos Regis & Sadre, Ramin & Pras, Aiko, 2013. "Flow whitelisting in SCADA networks," International Journal of Critical Infrastructure Protection, Elsevier, vol. 6(3), pages 150-158.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Monzer, Mohamad-Houssein & Beydoun, Kamal & Ghaith, Alaa & Flaus, Jean-Marie, 2022. "Model-based IDS design for ICSs," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    2. Davide Berardi & Franco Callegati & Andrea Giovine & Andrea Melis & Marco Prandini & Lorenzo Rinieri, 2023. "When Operation Technology Meets Information Technology: Challenges and Opportunities," Future Internet, MDPI, vol. 15(3), pages 1-16, February.
    3. Rahman, Ayesha & Mustafa, Ghulam & Khan, Abdul Qayyum & Abid, Muhammad & Durad, Muhammad Hanif, 2022. "Launch of denial of service attacks on the modbus/TCP protocol and development of its protection mechanisms," International Journal of Critical Infrastructure Protection, Elsevier, vol. 39(C).
    4. Fatima Salahdine & Naima Kaabouch, 2019. "Social Engineering Attacks: A Survey," Future Internet, MDPI, vol. 11(4), pages 1-17, April.
    5. Genge, Béla & Graur, Flavius & Haller, Piroska, 2015. "Experimental assessment of network design approaches for protecting industrial control systems," International Journal of Critical Infrastructure Protection, Elsevier, vol. 11(C), pages 24-38.
    6. Haller, Piroska & Genge, Béla & Duka, Adrian-Vasile, 2019. "On the practical integration of anomaly detection techniques in industrial control applications," International Journal of Critical Infrastructure Protection, Elsevier, vol. 24(C), pages 48-68.
    7. Jarmakiewicz, Jacek & Parobczak, Krzysztof & Maślanka, Krzysztof, 2017. "Cybersecurity protection for power grid control infrastructures," International Journal of Critical Infrastructure Protection, Elsevier, vol. 18(C), pages 20-33.
    8. Luca Foschini & Valentina Mignardi & Rebecca Montanari & Domenico Scotece, 2021. "An SDN-Enabled Architecture for IT/OT Converged Networks: A Proposal and Qualitative Analysis under DDoS Attacks," Future Internet, MDPI, vol. 13(10), pages 1-19, October.
    9. Berghout, Tarek & Benbouzid, Mohamed, 2022. "EL-NAHL: Exploring labels autoencoding in augmented hidden layers of feedforward neural networks for cybersecurity in smart grids," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    10. Wang, Wu & Harrou, Fouzi & Bouyeddou, Benamar & Senouci, Sidi-Mohammed & Sun, Ying, 2022. "Cyber-attacks detection in industrial systems using artificial intelligence-driven methods," International Journal of Critical Infrastructure Protection, Elsevier, vol. 38(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ijocip:v:42:y:2023:i:c:s1874548223000288. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/international-journal-of-critical-infrastructure-protection .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.