Advanced metering infrastructures: security risks and mitigation

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

doi:10.1145/3407023.3409312

Advanced metering infrastructures: security risks and mitigation

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

University of Peloponnese

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

282 Downloads (Pure)

Abstract

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 language	English
Title of host publication	Proceedings of the 15th International Conference on Availability, Reliability and Security, ARES 2020
Publisher	Association for Computing Machinery, Inc
Number of pages	8
ISBN (Electronic)	9781450388337
DOIs	https://doi.org/10.1145/3407023.3409312
Publication status	Published - 25 Aug 2020
Event	15th International Conference on Availability, Reliability and Security - Online, Ireland Duration: 25 Aug 2020 → 28 Aug 2020

Publication series

Name	ACM International Conference Proceedings Series
Publisher	ACM

Conference

Conference	15th International Conference on Availability, Reliability and Security
Abbreviated title	ARES 2020
Country/Territory	Ireland
Period	25/08/20 → 28/08/20

Keywords

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

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1145/3407023.3409312

Advanced Metering Infrastructures
© ACM 2020. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in Proceedings of the 15th International Conference on Availability, Reliability and Security, https://doi.org/10.1145/3407023.3409312.
Accepted author manuscript (Post-print), 634 KB

Cite this

Bendiab, G., Grammatikakis, K. P., Koufos, I., Kolokotronis, N., & Shiaeles, S. (2020). Advanced metering infrastructures: security risks and mitigation. In Proceedings of the 15th International Conference on Availability, Reliability and Security, ARES 2020 Article 113 (ACM International Conference Proceedings Series). Association for Computing Machinery, Inc. https://doi.org/10.1145/3407023.3409312

@inproceedings{0616d9fa94f84317a08a49e8372672a6,

title = "Advanced metering infrastructures: security risks and mitigation",

abstract = "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.",

keywords = "Attack mitigation, Cyber-security, Graphical security models, Intrusion detection, Malware detection, Power grid, noissn",

author = "Gueltoum Bendiab and Grammatikakis, {Konstantinos Panagiotis} and Ioannis Koufos and Nicholas Kolokotronis and Stavros Shiaeles",

note = "No ISSN found.; 15th International Conference on Availability, Reliability and Security, ARES 2020 ; Conference date: 25-08-2020 Through 28-08-2020",

year = "2020",

month = aug,

day = "25",

doi = "10.1145/3407023.3409312",

language = "English",

series = "ACM International Conference Proceedings Series",

publisher = "Association for Computing Machinery, Inc",

booktitle = "Proceedings of the 15th International Conference on Availability, Reliability and Security, ARES 2020",

}

Bendiab, G, Grammatikakis, KP, Koufos, I, Kolokotronis, N & Shiaeles, S 2020, Advanced metering infrastructures: security risks and mitigation. in Proceedings of the 15th International Conference on Availability, Reliability and Security, ARES 2020., 113, ACM International Conference Proceedings Series, Association for Computing Machinery, Inc, 15th International Conference on Availability, Reliability and Security, Ireland, 25/08/20. https://doi.org/10.1145/3407023.3409312

Advanced metering infrastructures: security risks and mitigation. / Bendiab, Gueltoum; Grammatikakis, Konstantinos Panagiotis; Koufos, Ioannis et al.
Proceedings of the 15th International Conference on Availability, Reliability and Security, ARES 2020. Association for Computing Machinery, Inc, 2020. 113 (ACM International Conference Proceedings Series).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Advanced metering infrastructures

T2 - 15th International Conference on Availability, Reliability and Security

AU - Bendiab, Gueltoum

AU - Grammatikakis, Konstantinos Panagiotis

AU - Koufos, Ioannis

AU - Kolokotronis, Nicholas

AU - Shiaeles, Stavros

N1 - No ISSN found.

PY - 2020/8/25

Y1 - 2020/8/25

N2 - 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.

AB - 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.

KW - Attack mitigation

KW - Cyber-security

KW - Graphical security models

KW - Intrusion detection

KW - Malware detection

KW - Power grid

KW - noissn

UR - http://www.scopus.com/inward/record.url?scp=85090328321&partnerID=8YFLogxK

UR - https://dl.acm.org/icps

U2 - 10.1145/3407023.3409312

DO - 10.1145/3407023.3409312

M3 - Conference contribution

AN - SCOPUS:85090328321

T3 - ACM International Conference Proceedings Series

BT - Proceedings of the 15th International Conference on Availability, Reliability and Security, ARES 2020

PB - Association for Computing Machinery, Inc

Y2 - 25 August 2020 through 28 August 2020

ER -

Bendiab G, Grammatikakis KP, Koufos I, Kolokotronis N, Shiaeles S. Advanced metering infrastructures: security risks and mitigation. In Proceedings of the 15th International Conference on Availability, Reliability and Security, ARES 2020. Association for Computing Machinery, Inc. 2020. 113. (ACM International Conference Proceedings Series). doi: 10.1145/3407023.3409312

Advanced metering infrastructures: security risks and mitigation

Abstract

Publication series

Conference

Keywords

UN SDGs

Access to Document

Fingerprint

Cite this