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Early Detection and Recovery Measures for Smart Grid Cyber-Resilience
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Author(s): Ismail Butun (Chalmers University of Technology, Sweden & Konya Food and Agriculture University, Turkey & Royal University of Technology, Sweden) and Alparslan Sari (University of Delaware, USA)
Copyright: 2021
Pages: 20
Source title:
Decision Support Systems and Industrial IoT in Smart Grid, Factories, and Cities
Source Author(s)/Editor(s): Ismail Butun (Chalmers University of Technology, Sweden & Konya Food and Agriculture University, Turkey & Royal University of Technology, Sweden)
DOI: 10.4018/978-1-7998-7468-3.ch005
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Abstract
The internet of things (IoT) has recently brought major technological advances in many domains, including the smart grid. Despite the simplicity and efficiency that IoT brings, there are also underlying risks that are slowing down its adoption. These risks are caused by the presence of legacy systems inside existing infrastructures that were built with no security in mind. In this chapter, the authors propose a method for early-stage detection of cyber-security incidents and protection against them through applicable security measures. This chapter introduces security techniques such as anomaly detection, threat investigation through a highly automated decision support system (DSS), as well as incident response and recovery for smart grid systems. The introduced framework can be applied to industrial environments such as cyber-threats targeting the production generator as well as the electricity smart meters, etc. The chapter also illustrates the framework's cyber-resilience against zero-day threats and its ability to distinguish between operational failures as well as cyber-security incidents.
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