论文标题
使用动态集群的大规模电力系统的移动目标网络攻击策略
A Moving-target Cyber-Attack Detection Strategy for Large-scale Power Systems using Dynamic Clustering
论文作者
论文摘要
近年来，电力系统的网络安全已成为日益关注的问题。为了保护电力系统免受恶意对手的侵害，需要利用复杂检测算法的先进防御策略。由此激励，在本文中，我们引入了一种基于动态聚类的主动防御方法。我们的检测策略采用了一种移动目标方法，其中首先将有关系统不同操作点的信息进行信息，以根据其传递功能特征随时间变化的转移功能特征进行聚类。然后，通过在同一群集内测量之间进行一系列相似性检查进行检测。即使攻击者在某个时间点对系统参数，模型和检测策略有广泛的了解，该方法也可以有效地检测网络攻击。我们提出的检测算法的有效性通过IEEE 24总线电源系统的数值示例证明。
In recent years, cyber-security of power systems has become a growing concern. To protect power systems from malicious adversaries, advanced defense strategies that exploit sophisticated detection algorithms are required. Motivated by this, in this paper we introduce an active defense method based on dynamic clustering. Our detection strategy uses a moving-target approach where information about the system's varying operating point is first used to cluster measurements according to their transfer function characteristics that change over time. Then, detection is carried out through series of similarity checks between measurements within the same cluster. The proposed method is effective in detecting cyber-attacks even when the attacker has extensive knowledge of the system parameters, model and detection policy at some point in time. The effectiveness of our proposed detection algorithm is demonstrated through a numerical example on the IEEE 24-bus power system.
