Inferring Anomaly Situation from Multiple Data Sources in Cyber Physical Systems
| Autor: | Marco Carli, Giuseppe Celozzi, Alessandro Neri, Federica Battisti, Sara Baldoni |
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| Přispěvatelé: | Springer Nature, Baldoni, S., Celozzi, G., Neri, A., Carli, M., Battisti, F. |
| Rok vydání: | 2021 |
| Předmět: |
Dependency (UML)
Exploit Computer science Cyber physical system Cyber-physical system Critical infrastructure protection 020206 networking & telecommunications Anomaly detection 02 engineering and technology Enterprise information security architecture Metrics Computer security computer.software_genre Article Proof of concept 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing computer |
| Zdroj: | Cyber-Physical Security for Critical Infrastructures Protection ISBN: 9783030697808 CPS4CIP Cyber-Physical Security for Critical Infrastructures Protection-First International Workshop, CPS4CIP 2020, Guildford, UK, September 18, 2020, Revised Selected Papers Cyber-Physical Security for Critical Infrastructures Protection Lecture Notes in Computer Science Lecture Notes in Computer Science-Cyber-Physical Security for Critical Infrastructures Protection |
| ISSN: | 0302-9743 1611-3349 |
| DOI: | 10.1007/978-3-030-69781-5_5 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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