Cyber physical systems are becoming ubiquitous devices in many fields thus creating the need for effective security measures. We propose to exploit their intrinsic dependency on the environment in which they are deployed to detect and mitigate anomalies. To do so, sensor measurements, network metrics, and contextual information are fused in a unified security architecture. In this paper, the model of the proposed framework is presented and a first proof of concept involving a telecommunication infrastructure case study is provided.

Inferring Anomaly Situation from Multiple Data Sources in Cyber Physical Systems

Baldoni S.;Battisti F.
2021

Abstract

Cyber physical systems are becoming ubiquitous devices in many fields thus creating the need for effective security measures. We propose to exploit their intrinsic dependency on the environment in which they are deployed to detect and mitigate anomalies. To do so, sensor measurements, network metrics, and contextual information are fused in a unified security architecture. In this paper, the model of the proposed framework is presented and a first proof of concept involving a telecommunication infrastructure case study is provided.
2021
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
1st International Workshop on Cyber-Physical Security for Critical Infrastructures Protection, CPS4CIP 2020 in conjunction with the European Symposium on Research in Computer Security, ESORICS 2020
978-3-030-69780-8
978-3-030-69781-5
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3418829
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