设计稀疏AC虚假数据注入攻击
Designing Sparse AC False Data Injection Attack
AI总结：
本文针对AC电力系统提出稀疏虚假数据注入攻击设计，通过构建混合整数非线性规划模型最小化篡改测量数，降低可检测性并实现状态估计偏差，在IEEE 57节点系统验证有效。
摘要：
虚假数据注入（FDI）攻击通过篡改测量数据导致错误的状态估计，构成重大威胁。尽管许多研究专注于设计DC FDI攻击，但由于在设计过程中引入非线性AC潮流的复杂性，鲜有研究涉及AC FDI攻击。此外，设计稀疏AC FDI攻击带来了另一个挑战，因为它涉及求解带有非凸约束的混合整数非线性规划问题，这本身就很困难。本文探讨了稀疏AC FDI攻击的设计与实现，攻击者策略性地选择最小测量集合进行篡改，同时保持AC潮流方程的非线性和相互依赖性。目标是最小化篡改的测量数量，从而降低攻击的可检测性，同时实现期望的状态估计误差。该问题被表述为混合整数非线性规划（MINLP）问题。二元变量指示被篡改测量的选择，连续变量表示测量值。优化问题旨在最小化二元变量数量，转化为稀疏攻击，同时确保攻击保持高效且难以检测。利用big-M方法和条件约束有效处理固定和可变测量参数。在标准IEEE 57节点测试系统上的仿真结果证明了稀疏AC FDI攻击在状态估计影响和成功实施所需最小测量数量方面的有效性。
英文摘要：
False Data Injection (FDI) attacks pose significant threats by manipulating measurement data, leading to incorrect state estimation. Although numerous studies have focused on designing DC FDI attacks, few have addressed AC FDI attacks due to the complexity of incorporating non-linear AC power flows in the design process. Additionally, designing a sparse AC FDI attack presents another challenge because it involves solving a mixed-integer nonlinear programming problem with nonconvex constraints, which is inherently difficult. This paper explores the design and implementation of a sparse AC FDI attack, where the attacker strategically selects a minimal set of measurements to manipulate while maintaining the nonlinearity and interdependence of AC power flow equations. The objective is to minimize the number of altered measurements, thereby reducing the attack's detectability while achieving the desired state estimation error. The problem is formulated as a Mixed Integer Nonlinear Programming (MINLP) problem. Binary variables indicate the selection of measurements to be manipulated, and continuous variables represent the measurement values. An optimization problem is designed to minimize the number of binary variables, translating into a sparse attack, while ensuring the attack remains efficient and hard to detect. The big-M method and conditional constraints are utilized to handle the fixed and variable measurement parameters effectively. Simulation results on the standard IEEE 57-bus test system demonstrate the efficacy of the sparse AC FDI attack in terms of its impact on state estimation and the minimal number of measurements required for successful implementation.
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