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基于攻击预测的电力CPS安全风险评估

A New Security Risk Assessment Method for Cyber Physical Power System Based on Attack Prediction

  • 摘要: 为准确评估当前电力信息物理系统(cyber physical system,CPS)的风险状态,针对信息、电力紧密耦合的特点,提出一种基于攻击预测的电力CPS风险评估方法。利用已检测到的攻击告警信息,基于隐马尔科夫模型(hidden Markov model,HMM)识别出可能的攻击场景,推测攻击者的攻击意图,分析其未来的攻击目标和概率。攻击预测结果表征着系统当前的攻击威胁状况,将其作为输入,结合传统的单域(信息域或物理域)风险评估方法计算单域风险,再基于电力CPS复杂网络模型评估跨域风险,融合二者的结果得到最终的风险值。基于智能配电网IEEE 33节点的仿真平台,对攻击预测方法以及安全风险评估方法进行了验证,证明了基于攻击预测的风险评估方法的可行性和合理性。

     

    Abstract: In order to analyze the current risk status of the cyber physical system (CPS) in power system, this paper proposes a risk assessment method for cyber physical power system based on attack prediction, with consideration of the close coupling characteristics of cyber system and power system. Firstly, we use alert message to identify the possible attack scenarios based on the hidden Markov model (HMM), and speculate the attacker's attack intention and analyze the next attack target and attack probability. The results of attack prediction represent the current attack threat status of the system and are used as the input of the risk assessment process. Secondly, we use the traditional single-domain (cyber domain or physical domain) risk assessment method to calculate the single-domain risk, and then assess the cross-domain risk based on the complex network model of cyber physical power system. The final risk value is obtained through integrating the results of both domains. Based on the smart distribution network simulation platform of IEEE 33 BUS, the attack prediction method and risk assessment method are verified, and the results have proved the feasibility and rationality of the attack prediction-based risk assessment method.

     

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