Multiobjective Optimization of Networked Switched Systems Subject to DoS Attack Using Artificial Bee Colony Algorithm

• Published in: IEEE transactions on control of network systems Vol. 10; no. 1; pp. 100 - 111
• Main Authors: Lian, Jie, Wang, Xiaohan, Wang, Dong, Jia, Peilin
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.03.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Continuously stirred tank reactors; Cost function; Denial of service attacks; DoS attack; Equilibrium conditions; Game theory; Games; Mathematical models; MOABC algorithm; Multiple objective analysis; Networked switched systems; Optimization; Pareto optimization; Performance indices; Physical layer; Search algorithms; Stackelberg game; Strategy; Subsystems; Swarm intelligence; Switched systems; Switches; Switching; Wireless communication; Wireless sensor networks
• ISSN: 2325-5870; 2372-2533
• DOI: 10.1109/TCNS.2022.3186624

In this article, the multiobjective optimization problem of networked switched systems under denial-of-service (DoS) attack is studied. DoS attacks launched by network layer attackers will affect the performance of switched systems in the physical layer, so it is necessary to deploy a defender to deal with it. Taking account of the properties of each switched subsystem and the characteristics of the attacker group composed of <inline-formula><tex-math notation="LaTeX">m</tex-math></inline-formula> DoS attackers, cost functions of the defender and <inline-formula><tex-math notation="LaTeX">m</tex-math></inline-formula> attackers are first constructed. Next, the Stackelberg game is used to analyze the game between the defender and attacker group, and the strategy sets of both sides are given by Stackelberg Equilibrium. In addition, for switched systems of the physical layer, the switching times and performance index are modeled as two objectives to be optimized. Based on the equilibrium condition of the network layer, the control input of switched systems is designed. Then, an encoding and decoding strategy of the switching signal is proposed to ensure that the multiobjective artificial bee colony (MOABC) algorithm can be applied to the multiobjective optimization problem of switched systems. Furthermore, the Pareto optimal solution set of switching signals is obtained by using the MOABC algorithm. Finally, the effectiveness of the strategy proposed in this article is verified through the networked continuous stirred tank reactor and a numerical simulation.