research-article

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IPAL: Breaking up Silos of Protocol-dependent and Domain-specific Industrial Intrusion Detection Systems

Authors:

Konrad Wolsing,

Antoine Saillard,

Martin HenzeAuthors Info & Claims

RAID '22: Proceedings of the 25th International Symposium on Research in Attacks, Intrusions and Defenses

Pages 510 - 525

https://doi.org/10.1145/3545948.3545968

Published: 26 October 2022 Publication History

All formats PDF

Abstract

The increasing interconnection of industrial networks exposes them to an ever-growing risk of cyber attacks. To reveal such attacks early and prevent any damage, industrial intrusion detection searches for anomalies in otherwise predictable communication or process behavior. However, current efforts mostly focus on specific domains and protocols, leading to a research landscape broken up into isolated silos. Thus, existing approaches cannot be applied to other industries that would equally benefit from powerful detection. To better understand this issue, we survey 53 detection systems and find no fundamental reason for their narrow focus. Although they are often coupled to specific industrial protocols in practice, many approaches could generalize to new industrial scenarios in theory. To unlock this potential, we propose IPAL, our industrial protocol abstraction layer, to decouple intrusion detection from domain-specific industrial protocols. After proving IPAL’s correctness in a reproducibility study of related work, we showcase its unique benefits by studying the generalizability of existing approaches to new datasets and conclude that they are indeed not restricted to specific domains or protocols and can perform outside their restricted silos.

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Cited By

Michaelides SLenz SVogt THenze M(2025)Secure integration of 5G in industrial networks: State of the art, challenges and opportunitiesFuture Generation Computer Systems10.1016/j.future.2024.107645166(107645)Online publication date: May-2025
https://doi.org/10.1016/j.future.2024.107645
Arreche OGuntur TAbdallah M(2024)XAI-IDS: Toward Proposing an Explainable Artificial Intelligence Framework for Enhancing Network Intrusion Detection SystemsApplied Sciences10.3390/app1410417014:10(4170)Online publication date: 14-May-2024
https://doi.org/10.3390/app14104170
Schuster FKönig H(2024)No Need for Details: Effective Anomaly Detection for Process Control Traffic in Absence of Protocol and Attack KnowledgeProceedings of the 27th International Symposium on Research in Attacks, Intrusions and Defenses10.1145/3678890.3678932(278-297)Online publication date: 30-Sep-2024
https://dl.acm.org/doi/10.1145/3678890.3678932
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Index Terms

IPAL: Breaking up Silos of Protocol-dependent and Domain-specific Industrial Intrusion Detection Systems
1. Networks
  1. Network services
    1. Network monitoring
  2. Network types
    1. Cyber-physical networks
2. Security and privacy
  1. Intrusion/anomaly detection and malware mitigation
    1. Intrusion detection systems

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RAID '22: Proceedings of the 25th International Symposium on Research in Attacks, Intrusions and Defenses

October 2022

536 pages

ISBN:9781450397049

DOI:10.1145/3545948

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Published: 26 October 2022

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RAID 2022: 25th International Symposium on Research in Attacks, Intrusions and Defenses

October 26 - 28, 2022

Limassol, Cyprus

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Cited By

Michaelides SLenz SVogt THenze M(2025)Secure integration of 5G in industrial networks: State of the art, challenges and opportunitiesFuture Generation Computer Systems10.1016/j.future.2024.107645166(107645)Online publication date: May-2025
https://doi.org/10.1016/j.future.2024.107645
Arreche OGuntur TAbdallah M(2024)XAI-IDS: Toward Proposing an Explainable Artificial Intelligence Framework for Enhancing Network Intrusion Detection SystemsApplied Sciences10.3390/app1410417014:10(4170)Online publication date: 14-May-2024
https://doi.org/10.3390/app14104170
Schuster FKönig H(2024)No Need for Details: Effective Anomaly Detection for Process Control Traffic in Absence of Protocol and Attack KnowledgeProceedings of the 27th International Symposium on Research in Attacks, Intrusions and Defenses10.1145/3678890.3678932(278-297)Online publication date: 30-Sep-2024
https://dl.acm.org/doi/10.1145/3678890.3678932
Barradas DNovo CPortela BRomeiro SSantos N(2024)Extending C2 Traffic Detection Methodologies: From TLS 1.2 to TLS 1.3-enabled MalwareProceedings of the 27th International Symposium on Research in Attacks, Intrusions and Defenses10.1145/3678890.3678921(181-196)Online publication date: 30-Sep-2024
https://dl.acm.org/doi/10.1145/3678890.3678921
Basels FWolsing KPadilla EBauer J(2024)Demo: Maritime Radar Systems under Attack. Help is on the Way!2024 IEEE 49th Conference on Local Computer Networks (LCN)10.1109/LCN60385.2024.10639793(1-4)Online publication date: 8-Oct-2024
https://doi.org/10.1109/LCN60385.2024.10639793
Sen ÖIvanov BKloos CZöll CLutat PHenze MUlbig AAndres M(2024)Simulation of multi-stage attack and defense mechanisms in smart gridsInternational Journal of Critical Infrastructure Protection10.1016/j.ijcip.2024.100727(100727)Online publication date: Dec-2024
https://doi.org/10.1016/j.ijcip.2024.100727
Bodenhausen JSorgatz CVogt TGrafflage KRötzel SRademacher MHenze M(2024)Securing Wireless Communication in Critical Infrastructure: Challenges and OpportunitiesMobile and Ubiquitous Systems: Computing, Networking and Services10.1007/978-3-031-63989-0_17(333-352)Online publication date: 19-Jul-2024
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Henze MOrtmann MVogt TUgus OHermann KNohr SLu ZMichaelides SMassonet ASchmitt R(2024)Towards Secure 5G Infrastructures for Production SystemsApplied Cryptography and Network Security Workshops10.1007/978-3-031-61489-7_14(198-203)Online publication date: 29-Jun-2024
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Alnajim AHabib SIslam MThwin SAlotaibi F(2023)A Comprehensive Survey of Cybersecurity Threats, Attacks, and Effective Countermeasures in Industrial Internet of ThingsTechnologies10.3390/technologies1106016111:6(161)Online publication date: 13-Nov-2023
https://doi.org/10.3390/technologies11060161
Sen ÖMalskorn PGlomb SHacker IHenze MUlbig A(2023)An Approach to Abstract Multi-stage Cyberattack Data Generation for ML-Based IDS in Smart Grids2023 IEEE Belgrade PowerTech10.1109/PowerTech55446.2023.10202747(01-10)Online publication date: 25-Jun-2023
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