Sherlock: A Dataset for Process-aware Intrusion Detection Research on Power Grid Networks
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arXiv
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| Auteurs principaux: | , , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866915233588576256 |
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| author | Wagner, Eric Bader, Lennart Wolsing, Konrad Serror, Martin |
| author_facet | Wagner, Eric Bader, Lennart Wolsing, Konrad Serror, Martin |
| contents | Physically distributed components and legacy protocols make the protection of power grids against increasing cyberattack threats challenging. Infamously, the 2015 and 2016 blackouts in Ukraine were caused by cyberattacks, and the German Federal Office for Information Security (BSI) recorded over 200 cyber incidents against the German energy sector between 2023 and 2024. Intrusion detection promises to quickly detect such attacks and mitigate the worst consequences. However, public datasets of realistic scenarios are vital to evaluate these systems. This paper introduces Sherlock, a dataset generated with the co-simulator Wattson. In total, Sherlock covers three scenarios with various attacks manipulating the process state by injecting malicious commands or manipulating measurement values. We additionally test five recently-published intrusion detection systems on Sherlock, highlighting specific challenges for intrusion detection in power grids. Dataset and documentation are available at https://sherlock.wattson.it/. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_06102 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Sherlock: A Dataset for Process-aware Intrusion Detection Research on Power Grid Networks Wagner, Eric Bader, Lennart Wolsing, Konrad Serror, Martin Cryptography and Security Networking and Internet Architecture Physically distributed components and legacy protocols make the protection of power grids against increasing cyberattack threats challenging. Infamously, the 2015 and 2016 blackouts in Ukraine were caused by cyberattacks, and the German Federal Office for Information Security (BSI) recorded over 200 cyber incidents against the German energy sector between 2023 and 2024. Intrusion detection promises to quickly detect such attacks and mitigate the worst consequences. However, public datasets of realistic scenarios are vital to evaluate these systems. This paper introduces Sherlock, a dataset generated with the co-simulator Wattson. In total, Sherlock covers three scenarios with various attacks manipulating the process state by injecting malicious commands or manipulating measurement values. We additionally test five recently-published intrusion detection systems on Sherlock, highlighting specific challenges for intrusion detection in power grids. Dataset and documentation are available at https://sherlock.wattson.it/. |
| title | Sherlock: A Dataset for Process-aware Intrusion Detection Research on Power Grid Networks |
| topic | Cryptography and Security Networking and Internet Architecture |
| url | https://arxiv.org/abs/2504.06102 |