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Towards a novel quantification approach based on smart grid network vulnerability score
Author(s) -
Ko Jongbin,
Lee Seokjun,
Shon Taeshik
Publication year - 2015
Publication title -
international journal of energy research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.808
H-Index - 95
eISSN - 1099-114X
pISSN - 0363-907X
DOI - 10.1002/er.3356
Subject(s) - computer science , smart grid , vulnerability (computing) , computer security , vulnerability assessment , the internet , grid , distributed computing , network security , function (biology) , engineering , world wide web , psychology , geometry , mathematics , evolutionary biology , psychological resilience , electrical engineering , psychotherapist , biology
Summary Smart grid, known as the system of systems, has progressed with more diverse network systems than existing Internet‐based networks. Although some of its internal components contain systems reminiscent of a general Internet environment, most of them have different characteristics in terms of their function and performance. Therefore, it is impractical to apply the same techniques for quantifying security vulnerabilities used in existing Internet environments to smart grid. Such techniques do not reflect the characteristics of smart grid networks. In addition, the existing quantification approaches to security vulnerability typically apply to vulnerabilities known in a target system itself or by generalizing attack paths that can occur in a target system. Therefore, it is difficult for these approaches to reflect the vulnerabilities in an environment such as smart grid, which has various heterogeneous systems and networks. In this paper, we consider various approaches to quantifying security vulnerabilities in smart grid network environments by analyzing the existing quantification approaches to security vulnerabilities, and we propose the smart grid network vulnerability score, a quantification approach to security vulnerability that can comprehensively display security threats by reflecting the characteristics of smart grid network. We verified the effectiveness and applicability of this proposed approach by applying it to the advanced metering infrastructure network, which is sensitive to the issues related to users in a number of smart grid network domains. Copyright © 2015 John Wiley & Sons, Ltd.