Research Article
Automated Configuration Synthesis for Resilient Smart Metering Infrastructure
@ARTICLE{10.4108/eai.10-9-2021.170948, author={Mohammad Ashiqur Rahman and Amarjit Datta and Ehab Al-Shaer}, title={Automated Configuration Synthesis for Resilient Smart Metering Infrastructure}, journal={EAI Endorsed Transactions on Security and Safety}, volume={8}, number={28}, publisher={EAI}, journal_a={SESA}, year={2021}, month={9}, keywords={Advanced metering infrastructure, configuration synthesis, resiliency, formal model}, doi={10.4108/eai.10-9-2021.170948} }
- Mohammad Ashiqur Rahman
Amarjit Datta
Ehab Al-Shaer
Year: 2021
Automated Configuration Synthesis for Resilient Smart Metering Infrastructure
SESA
EAI
DOI: 10.4108/eai.10-9-2021.170948
Abstract
An Advanced Metering Infrastructure (AMI) comprises a large number of smart meters along with heterogeneous cyber-physical components that are interconnected through different communication media, protocols, and delivery modes for transmitting usage reports or control commands between meters and the utility. Due to misconfigurations or lack of security controls, there can be operational disruptions leading to economic damage in an AMI. Therefore, the resiliency of an AMI is crucial. In this paper, we present an automated configuration synthesis framework that mitigates potential threats by eliminating misconfigurations and keeps the damage limited under contingencies by introducing robustness. We formally model AMI configurations, including operational integrity and robustness properties considering the interdependencies among AMI devices’ configurations, attacks or failures, and resiliency guidelines. We implement the model using Satisfiability Modulo Theories (SMT) and demonstrate its execution on an example case study that illustrates the synthesis of AMI configurations satisfying resiliency requirements. We also evaluate the framework on synthetic AMI networks.
Copyright © 2021 M. A. Rahman et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.