Advanced metering infrastructures: security risks and mitigation

Gueltoum Bendiab, Konstantinos Panagiotis Grammatikakis, Ioannis Koufos, Nicholas Kolokotronis, Stavros Shiaeles

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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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.

Original languageEnglish
Title of host publicationProceedings of the 15th International Conference on Availability, Reliability and Security, ARES 2020
PublisherAssociation for Computing Machinery, Inc
Number of pages8
ISBN (Electronic)9781450388337
Publication statusPublished - 25 Aug 2020
Event15th International Conference on Availability, Reliability and Security - Online, Ireland
Duration: 25 Aug 202028 Aug 2020

Publication series

NameACM International Conference Proceedings Series


Conference15th International Conference on Availability, Reliability and Security
Abbreviated titleARES 2020


  • Attack mitigation
  • Cyber-security
  • Graphical security models
  • Intrusion detection
  • Malware detection
  • Power grid
  • noissn


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