DDoS Defense Method in Software-Defined Space-Air-Ground Network from Dynamic Bayesian Game Perspective. (7th January 2022)

• Record Type: Journal Article
• Authors: Li, Zhaobin; Yang, Bin; Zhang, Xinyu; Guo, Chao
• Other Names: Wang Zhen Academic Editor.
• Is Part Of: Security and communication networks. Volume 2022(2022)
• Publication Date: 2022-01-07
• Subjects: Computer networks -- Security measures -- Periodicals; Computer security -- Periodicals; Cryptography -- Periodicals; 005.805
• DOI: 10.1155/2022/1886516
• Languages: English
• ISSNs: 1939-0114

Abstract

Abstract : The centralized management of Software-Defined Network (SDN) brings convenience to Space-Air-Ground Integrated Networks (SAGIN), which also makes it vulnerable to Distributed Denial of Service (DDoS). At present, the popular detection methods are based on machine learning, but most of them are fixed detection strategies with high overhead and real-time control, so the efficiency is not high. This paper designs different defense methods for different DDoS attacks and constructs a multitype DDoS defense model based on a dynamic Bayesian game in the Software-Defined Space-Air-Ground Integrated Networks (SD-SAGIN). The proposed game model's Nash equilibrium is solved based on the different costs and payoffs of each method. We simulated the attack and defense of DDoS in Ryu controller and Mininet. The results show that, under our model, the attacker and defender's strategies are in a dynamic balance, and the controller can effectively reduce the defense cost while ensuring detection accuracy. Compared with the existing traditional Support Vector Machine (SVM) defense method, the performance of the proposed method is better, and it provides one of the references for DDoS defense in SD-SAGIN.