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Autori:Davide Cerotti
Daniele Codetta Raiteri
Giovanna Dondossola
Lavinia Egidi
Giuliana Franceschinis
Luigi Portinale
Roberta Terruggia
Area Scientifica:Uncertain Reasoning
Probabilistic Graphical Models
Computer Security
Dependability and Reliability
Titolo:A Modular Infrastructure for the Validation of Cyberattack Detection Systems
Apparso su:Power Systems Cybersecurity: Methods, Concepts and Best Practices
Pagine:311-336
Editore:Springer
Anno:2023
Tipo Pubblicazione:Chapter of Book
URL:https://link.springer.c...0.1007/978-3-031-20360-2_13
Sommario:We propose a framework for the evaluation of cyberattack detection systems in which theoretical results can be tested in a realistic setup. We emulate a power control infrastructure, an attacker and a monitoring system. In this controlled environment, through a modular approach, it is possible to evaluate a variety of detection models: we inject adversarial activity, collect logs from the systems, analyze such logs and produce evidences that are later processed by artificial intelligence models that can raise alerts, and give diagnostic or predictive information. In particular, we test our framework with detection models based on Dynamic Bayesian Networks, that take into account the evolution of adversarial activities over time. The testbed allows us to effectively test the adequacy of the detection mechanisms for early warning of suspicious events; currently, it includes man-in-the-middle attacks and false data injection.