Anomaly Detection in Water Management Systems

Raciti, Massimiliano; Cucurull, Jordi; Nadjm‐Tehrani, Simin

doi:10.1007/978-3-642-28920-0_6

Cited by 36 publications

(28 citation statements)

References 22 publications

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“…The second approach to event detection is based on signal processing and data driven techniques [10,[15][16][17][18][19][20]. For example, Hart et al [15] reported a linear prediction filter (LPF).…”

Section: Introductionmentioning

confidence: 99%

“…The MED approach provides a measure of the distance between the sampled water quality and the previously measured samples contained in the history window. Allgeier et al [17] and Raciti et al [18] utilized artificial neural networks (ANN) and support vector machines (SVM) to classify water quality data into normal and anomalous classes after supervised learning training. Perelman et al [19] and Arad et al [20] reported a general framework that integrates a data-driven estimation model with sequential probability updating to detect quality faults in water distribution systems using multivariate water quality time series.…”

Section: Introductionmentioning

confidence: 99%

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Performance Evaluation for a Contamination Detection Method Using Multiple Water Quality Sensors in an Early Warning System

Han

Liu

Smith

2015

Water

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Abstract:In this approach, a method utilizing data series from multivariate parameters to detect contaminant events is discussed and evaluated. Eight water quality sensors (pH, turbidity, conductivity, temperature, oxidation reduction potential, UV-254, nitrate and phosphate) are used in this study and the most commonly used herbicide, glyphosate, is selected as the test contaminant. Variations of all parameters are recorded in real time at different concentrations. The results from the experiment and analysis show that the proposed method with suitable optimization can detect a glyphosate contamination less than 5 min after the introduction of the contaminant using responses from online water quality sensors. The average true positive rate is 95.5%. The study also discusses the impact of the number of sensors on detection performance. The results show that if the number of sensors is reduced from 8 to 5, the true positive rate performance is still good. This indicates that the method is flexible and can be applied using a smaller number of sensors to reduce monitoring costs.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Performance Evaluation for a Contamination Detection Method Using Multiple Water Quality Sensors in an Early Warning System

Han

Liu

Smith

2015

Water

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“…Secondly, the use of anomaly detection in water management systems is discussed by Raciti et al, [179]. Their research is motivated by the concern over the quality of drinking water and as part of the critical infrastructure grouping, water supply security is at risk from cyber-threats.…”

Section: Existing Behavioural Researchmentioning

confidence: 99%

“…In the case of misuse detection, the inability to identify attacks, which have not previously taken place meaning that it is always one step behind new and emerging attacks, is the main problem. However, in the case of anomaly detection, new attacks can be uncovered but there is a dependence on referencing behaviour back to a control model of normality [179].…”

Section: Existing Behavioural Researchmentioning

confidence: 99%

Behavioural Observation for Critical Infrastructure Security Support

Hurst

Merabti

Fergus

2013

2013 European Modelling Symposium

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“…It has previously been successfully used as a component in critical information infrastructure protection [22], as well as a means of detecting contaminants in drinking water [23]. Since anomaly detection is effective when searching for irregular patterns in large data sets, we have chosen ADWICE as the basis of our DLP approach.…”

Section: B Adwicementioning

confidence: 99%

Best-effort Data Leakage Prevention in inter-organizational tactical MANETs

Sigholm

Raciti

2012

MILCOM 2012 - 2012 IEEE Military Communications Conference

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Abstract-Reconfigurable Radio Systems (RRS), based on Software Defined Radio (SDR) and Mobile Ad-hoc Network (MANET) technologies, offer considerable advantages for military operations, such as increased network survivability and interoperability. The RRS-based Common Tactical Radio System (GTRS), currently in development by the Swedish Armed Forces, is designed for use in diverse geographical settings and for purposes varying from international combat missions to national contingency operations. However, protecting these networks from attacks and safeguarding the carried information against leaks is an ongoing research challenge, especially in combined scenarios where tactical data may flow across organizational boundaries. This paper presents a best-effort approach to Data Leakage Prevention (DLP) for inter-organizational RRS-based networks.The proposed architecture makes use of data mining techniques and an efficient n-dimensional clustering algorithm which has previously been successfully used for real-time anomaly detection in critical infrastructure protection. The DLP architecture is developed as an extension to the GTRS system, modeled and simulated in OPNET™ Modeler. Our results show that common data leaks can be efficiently identified by the proposed scheme, while keeping the important false positive rate at a very low level.

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Anomaly Detection in Water Management Systems

Cited by 36 publications

References 22 publications

Performance Evaluation for a Contamination Detection Method Using Multiple Water Quality Sensors in an Early Warning System

Performance Evaluation for a Contamination Detection Method Using Multiple Water Quality Sensors in an Early Warning System

Behavioural Observation for Critical Infrastructure Security Support

Best-effort Data Leakage Prevention in inter-organizational tactical MANETs

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