Monitoring platforms are widely employed for protecting critical systems. The accurate design of these infrastructures against accidental and malicious threats is a crucial activity of their life-cycle. The early recognition of possible attack sources is still an open challenge for the current research. This work aims to exploit model-driven practices and Bayesian Networks to evaluate the impact of monitoring platforms over the protection of modern transport networks and to recognize the most probable attack source during operational phases. As this approach is generally applicable to different transport systems, to better highlight the potentialities of the approach, an instance within the domain of the water distribution networks is presented. Threats against the quality of water, such as chemical and bacteriological attacks aiming at introducing dangerous substances in the transport system, are considered in this work.

Computer-aided security assessment of water networks monitoring platforms

Nardone, R.;
2020-01-01

Abstract

Monitoring platforms are widely employed for protecting critical systems. The accurate design of these infrastructures against accidental and malicious threats is a crucial activity of their life-cycle. The early recognition of possible attack sources is still an open challenge for the current research. This work aims to exploit model-driven practices and Bayesian Networks to evaluate the impact of monitoring platforms over the protection of modern transport networks and to recognize the most probable attack source during operational phases. As this approach is generally applicable to different transport systems, to better highlight the potentialities of the approach, an instance within the domain of the water distribution networks is presented. Threats against the quality of water, such as chemical and bacteriological attacks aiming at introducing dangerous substances in the transport system, are considered in this work.
2020
Bayesian networks, Model driven engineering, Water distribution networks, Critical infrastructure monitoring, System monitoring assessment
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12318/79480
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