Umar Sani, Felemban Muhamad
Computer Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia.
Sensors (Basel). 2021 Apr 2;21(7):2478. doi: 10.3390/s21072478.
Cyber-security of modern power systems has captured a significant interest. The vulnerabilities in the cyber infrastructure of the power systems provide an avenue for adversaries to launch cyber attacks. An example of such cyber attacks is False Data Injection Attacks (FDIA). The main contribution of this paper is to analyze the impact of FDIA on the cost of power generation and the physical component of the power systems. Furthermore, We introduce a new FDIA strategy that intends to maximize the cost of power generation. The viability of the attack is shown using simulations on the standard IEEE bus systems using the MATPOWER MATLAB package. We used the genetic algorithm (GA), simulated annealing (SA) algorithm, tabu search (TS), and particle swarm optimization (PSO) to find the suitable attack targets and execute FDIA in the power systems. The proposed FDIA increases the generation cost by up to 15.6%, 45.1%, 60.12%, and 74.02% on the 6-bus, 9-bus, 30-bus, and 118-bus systems, respectively. Finally, a rule-based FDIA detection and prevention mechanism is proposed to mitigate such attacks on power systems.
现代电力系统的网络安全已引起广泛关注。电力系统网络基础设施中的漏洞为对手发动网络攻击提供了途径。虚假数据注入攻击（FDIA）就是此类网络攻击的一个例子。本文的主要贡献在于分析FDIA对发电成本和电力系统物理组件的影响。此外，我们引入了一种新的FDIA策略，旨在使发电成本最大化。通过使用MATPOWER MATLAB软件包在标准IEEE母线系统上进行仿真，展示了该攻击的可行性。我们使用遗传算法（GA）、模拟退火（SA）算法、禁忌搜索（TS）和粒子群优化（PSO）来找到合适的攻击目标并在电力系统中执行FDIA。所提出的FDIA在6母线、9母线、30母线和118母线系统上分别使发电成本提高了15.6%、45.1%、60.12%和74.02%。最后，提出了一种基于规则的FDIA检测与预防机制，以减轻对电力系统的此类攻击。
