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A General Framework for the Assessment of Power System Vulnerability to Malicious Attacks
Author(s) -
Piccinelli R.,
Sansavini G.,
Lucchetti R.,
Zio E.
Publication year - 2017
Publication title -
risk analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.972
H-Index - 130
eISSN - 1539-6924
pISSN - 0272-4332
DOI - 10.1111/risa.12781
Subject(s) - offensive , computer security , vulnerability (computing) , computer science , identification (biology) , game theory , bayesian game , denial of service attack , vulnerability assessment , power (physics) , risk analysis (engineering) , operations research , engineering , sequential game , mathematical economics , business , mathematics , the internet , psychology , botany , physics , quantum mechanics , psychological resilience , world wide web , psychotherapist , biology
Abstract The protection and safe operations of power systems heavily rely on the identification of the causes of damage and service disruption. This article presents a general framework for the assessment of power system vulnerability to malicious attacks. The concept of susceptibility to an attack is employed to quantitatively evaluate the degree of exposure of the system and its components to intentional offensive actions. A scenario with two agents having opposing objectives is proposed, i.e., a defender having multiple alternatives of protection strategies for system elements, and an attacker having multiple alternatives of attack strategies against different combinations of system elements. The defender aims to minimize the system susceptibility to the attack, subject to budget constraints; on the other hand, the attacker aims to maximize the susceptibility. The problem is defined as a zero‐sum game between the defender and the attacker. The assumption that the interests of the attacker and the defender are opposite makes it irrelevant whether or not the defender shows the strategy he/she will use. Thus, the approaches “leader–follower game” or “simultaneous game” do not provide differences as far as the results are concerned. The results show an example of such a situation, and the von Neumann theorem is applied to find the (mixed) equilibrium strategies of the attacker and of the defender.