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Modeling and Analysis of MDP-based Security Risk Assessment System for Smart Grids

机译:基于MDP的智能电网安全风险评估系统建模与分析

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The recent advances in communications and networking technologies have made the electricity service provisioning more convenient, affordable and manageable through the realization of Smart Grids. However, these cyber-physical systems have become vulnerable to security attacks leading to service disruptions. To address this challenge, it is crucial to design, model and implement a robust security risk management solution to protect the Smart Grids in the event of a security attack. In this paper we propose, implement and evaluate a Probabilistic Model Checking (PMC) system to model the security attack process. In particular, we model the attacker behavior through a Markov Decision Process (MDP) which non-deterministically and probabilistically captures the attack process in a Smart Grid system consisting of eight important components. Two major scenarios are presented, considering the non-persistence and persistence attacker behaviors. The parameters used in the PRISM tool to evaluate the robustness of the proposed model were the Probability of successful attack, Attack costs, and Number of attack attempts. The proposed implementation provides useful insights into the best possible defense or preventive mechanisms that can be adopted by the security manager in the event of a specific security attack.
机译:通过实现智能电网,通信和网络技术的最新发展使电力服务供应更加方便,可负担和可管理。但是,这些网络物理系统已经变得容易受到安全攻击的破坏,从而导致服务中断。为了应对这一挑战,设计,建模和实施强大的安全风险管理解决方案以在发生安全攻击时保护智能电网至关重要。在本文中,我们提出,实施和评估概率模型检查(PMC)系统以对安全攻击过程进行建模。尤其是,我们通过马尔可夫决策过程(MDP)对攻击者的行为进行建模,该过程在由八个重要组件组成的智能电网系统中非确定性和概率性地捕获了攻击过程。考虑到非持久性和持久性攻击者的行为,提出了两种主要方案。 PRISM工具中用于评估所提出模型的鲁棒性的参数是成功攻击的概率,攻击成本和攻击尝试次数。所提出的实施方案提供了对最佳防御或预防机制的有用见解,在发生特定安全攻击时,安全管理器可以采用最佳防御或预防机制。

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