An Approach to Detect the Cyber-Physical Attack on Water Distribution System
Abstract
The dependency of modern water distribution systems (WDS) on computer and cyber control make the systems more susceptible to cyber-physical attack. While the cyber-physical attacks can be classified into several categories such as direct and indirect, the main purpose of the attack is to disrupt the operation of the WDS. Attack changes normal flow patterns and operations of the system leaving its signature behind in the datasets. Understanding normal system operations and hydraulics and system relationships are thus important to identify any anomalous behavior in the system. This paper presents an algorithm where three modules are developed based on the consistency and pattern of data and hydraulics and system relationships. These modules are interlinked with some logical statements to identify, detect, and quantify the magnitude of any cyber-physical attack. The algorithm which has been applied to a mid-sized network known as C-Town network can successfully characterize and detects the cyber-physical attacks. The location (WDS component), duration, and the magnitude of the cyber-physical attack are identified through the use of the algorithm.
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The algorithm of Pasha et al. (2017) issued just a few false alarms but lacked sensitivity, failing to flag the system as under attack for the entire duration of the events.
“On the other hand, the algorithm of Pasha et al. (2017) issued just a few false alarms, but it lacked sensitivity, thus failing to flag the system as under attack for the entire duration of the events.”
From Battle of the Attack Detection Algorithms: Disclosing Cyber Attacks on Water Distribution Networks (2018) · cites this paper as Pasha et al. (2017)
The score S for Chandy et al. (2017) is 0.802 and for Pasha et al. (2017) is 0.773.
“Their score S is equal to 0.802 and 0.773, respectively.”
From Battle of the Attack Detection Algorithms: Disclosing Cyber Attacks on Water Distribution Networks (2018) · cites this paper as Pasha et al. (2017)
With the exception of Brentan et al. (2017) and Pasha et al. (2017), there appears to be a strong correlation between time-to-detection and classification score.
“With the exception of Brentan et al. (2017) and Pasha et al. (2017), there appears to be a strong correlation between these two metrics (see Fig -ure 3).”
From Battle of the Attack Detection Algorithms: Disclosing Cyber Attacks on Water Distribution Networks (2018) · cites this paper as Pasha et al. (2017)
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- Authors
- Pasha, M. F. K., Kc, B., & Somasundaram, S. L.
- Affiliations
- California State University, Fresno (US)
- Venue
- World Environmental and Water Resources Congress 2017
- Publisher
- American Society of Civil Engineers
- Published
- 2017-05-18
- Pages
- 703-711
- OpenAlex
- W2614385421
- Cited by
- 24
- References
- 3
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 3 · 2023: 4 · 2022: 4 · 2021: 5 · 2020: 2 · 2019: 1 · 2018: 2
- FWCI
- 4.14
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- World Environmental and Water Resources Congress (EWRI) (publishedVersion)
- Topics
- Physical Sciences › Engineering › Civil and Structural Engineering › Water Systems and Optimization
- Physical Sciences › Engineering › Control and Systems Engineering › Smart Grid Security and Resilience
- Physical Sciences › Engineering › Civil and Structural Engineering › Infrastructure Resilience and Vulnerability Analysis
- Keywords
- cyber-physical attacks, water distribution systems, attack detection, anomaly detection, data consistency, attack localization
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