Toward the Integration of Cyber and Physical Security Monitoring Systems for Critical Infrastructures
Critical Infrastructures (CIs) are sensible targets. They could be physically damaged by natural or human actions, causing service disruptions, economic losses, and, in some extreme cases, harm to people. They, therefore, need a high level of protection against possible unintentional and intentional...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-10-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/21/21/6970 |
| _version_ | 1827677920160645120 |
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| author | Alessandro Fausto Giovanni Battista Gaggero Fabio Patrone Paola Girdinio Mario Marchese |
| author_facet | Alessandro Fausto Giovanni Battista Gaggero Fabio Patrone Paola Girdinio Mario Marchese |
| author_sort | Alessandro Fausto |
| collection | DOAJ |
| description | Critical Infrastructures (CIs) are sensible targets. They could be physically damaged by natural or human actions, causing service disruptions, economic losses, and, in some extreme cases, harm to people. They, therefore, need a high level of protection against possible unintentional and intentional events. In this paper, we show a logical architecture that exploits information from both physical and cybersecurity systems to improve the overall security in a power plant scenario. We propose a Machine Learning (ML)-based anomaly detection approach to detect possible anomaly events by jointly correlating data related to both the physical and cyber domains. The performance evaluation showed encouraging results—obtained by different ML algorithms—which highlights how our proposed approach is able to detect possible abnormal situations that could not have been detected by using only information from either the physical or cyber domain. |
| first_indexed | 2024-03-10T05:53:28Z |
| format | Article |
| id | doaj.art-f71a1211fb2a405d83f82b6a9dfa632f |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T05:53:28Z |
| publishDate | 2021-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-f71a1211fb2a405d83f82b6a9dfa632f2023-11-22T21:34:39ZengMDPI AGSensors1424-82202021-10-012121697010.3390/s21216970Toward the Integration of Cyber and Physical Security Monitoring Systems for Critical InfrastructuresAlessandro Fausto0Giovanni Battista Gaggero1Fabio Patrone2Paola Girdinio3Mario Marchese4DITEN Department, University of Genoa, 16145 Genoa, ItalyDITEN Department, University of Genoa, 16145 Genoa, ItalyDITEN Department, University of Genoa, 16145 Genoa, ItalyDITEN Department, University of Genoa, 16145 Genoa, ItalyDITEN Department, University of Genoa, 16145 Genoa, ItalyCritical Infrastructures (CIs) are sensible targets. They could be physically damaged by natural or human actions, causing service disruptions, economic losses, and, in some extreme cases, harm to people. They, therefore, need a high level of protection against possible unintentional and intentional events. In this paper, we show a logical architecture that exploits information from both physical and cybersecurity systems to improve the overall security in a power plant scenario. We propose a Machine Learning (ML)-based anomaly detection approach to detect possible anomaly events by jointly correlating data related to both the physical and cyber domains. The performance evaluation showed encouraging results—obtained by different ML algorithms—which highlights how our proposed approach is able to detect possible abnormal situations that could not have been detected by using only information from either the physical or cyber domain.https://www.mdpi.com/1424-8220/21/21/6970critical infrastructurecybersecurityphysical securityanomaly detectionmachine learning |
| spellingShingle | Alessandro Fausto Giovanni Battista Gaggero Fabio Patrone Paola Girdinio Mario Marchese Toward the Integration of Cyber and Physical Security Monitoring Systems for Critical Infrastructures Sensors critical infrastructure cybersecurity physical security anomaly detection machine learning |
| title | Toward the Integration of Cyber and Physical Security Monitoring Systems for Critical Infrastructures |
| title_full | Toward the Integration of Cyber and Physical Security Monitoring Systems for Critical Infrastructures |
| title_fullStr | Toward the Integration of Cyber and Physical Security Monitoring Systems for Critical Infrastructures |
| title_full_unstemmed | Toward the Integration of Cyber and Physical Security Monitoring Systems for Critical Infrastructures |
| title_short | Toward the Integration of Cyber and Physical Security Monitoring Systems for Critical Infrastructures |
| title_sort | toward the integration of cyber and physical security monitoring systems for critical infrastructures |
| topic | critical infrastructure cybersecurity physical security anomaly detection machine learning |
| url | https://www.mdpi.com/1424-8220/21/21/6970 |
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