Advanced Metering Infrastructures: Security Risks and Mitigation
Energy providers are moving to the smart meter era, encouraging consumers to install, free of charge, these devices in their homes, automating consumption readings submission and making consumers life easier. However, the increased deployment of such smart devices brings a lot of security and privac...
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| Veröffentlicht in: | arXiv.org 2021-05 |
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| creator | Bendiab, Gueltoum Konstantinos-Panagiotis Grammatikakis Koufos, Ioannis Kolokotronis, Nicholas Shiaeles, Stavros |
| description | Energy providers are moving to the smart meter era, encouraging consumers to install, free of charge, these devices in their homes, automating consumption readings submission and making consumers life easier. However, the increased deployment of such smart devices brings a lot of security and privacy risks. In order to overcome such risks, Intrusion Detection Systems are presented as pertinent tools that can provide network-level protection for smart devices deployed in home environments. In this context, this paper is exploring the problems of Advanced Metering Infrastructures (AMI) and proposing a novel Machine Learning (ML) Intrusion Prevention System (IPS) to get optimal decisions based on a variety of factors and graphical security models able to tackle zero-day attacks. |
| doi_str_mv | 10.48550/arxiv.2105.04272 |
| format | Article |
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| subjects | Advanced metering infrastructure Computer Science - Cryptography and Security Consumers Electronic devices Intrusion detection systems Machine learning Security |
| title | Advanced Metering Infrastructures: Security Risks and Mitigation |
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