4.5 Article

Assessment of potential security risks in advanced metering infrastructure using the OCTAVE Allegro approach

Journal

COMPUTERS & ELECTRICAL ENGINEERING
Volume 108, Issue -, Pages -

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compeleceng.2023.108667

Keywords

Critical infrastructure; Advanced metering infrastructure; Security risk assessment; AMI security vulnerability; OCTAVE Allegro; Information container; Smart meters

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One of the crucial components of a smart grid is the advanced metering infrastructure (AMI), which integrates information and communication technologies with a conventional electricity grid. An information security risk assessment (ISRA) process must be carried out to identify potential risks before applying any security measures to the AMI system. This study contributes to AMI security by assessing potential security risks using the OCTAVE Allegro (OA) approach, identifying 11 risk scenarios that affect the confidentiality, integrity, or availability of the AMI system, and recommending risk mitigation approaches.
One of the crucial components of a smart grid is the advanced metering infrastructure (AMI), which integrates information and communication technologies with a conventional electricity grid. Due to the importance of an AMI system and the vital data that it stores, an information security risk assessment (ISRA) process must be carried out to identify potential risks before applying any security measures. This study contributes to AMI security by assessing the potential security risks using the OCTAVE Allegro (OA) approach. OA is selected as an appropriate approach based on a comparative study of ISRA methods. The comparison process aligns the AMI requirements with the capabilities of the ISRA methods. To analyze any potential security risks, an AMI system is evaluated through the eight steps of the OA methodology. Through the OA implementation, eleven risk scenarios are identified that affect the confidentiality, integrity, or availability of an AMI system. For completeness, the study recommends risk mitigation approaches to limit the identified risks associated with an AMI system.

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