Model design artificial intelligence and research of adaptive network intrusion detection and defense system using fuzzy logic

Issue title: Ethical Computational Intelligence for Cyber Market

Guest editors: Oscar Sanjuán Martínez, Giuseppe Fenza and Ruben Gonzalez Crespo

Article type: Research Article

Authors: Luo, Xiaolin^{; *}

Affiliations: Zibo Vocational Institute, Zibo, China

Correspondence: [*] Corresponding author. Xiaolin Luo, Zibo Vocational Institute, Zibo 255314, China. E-mail: z655566@126.com.

Abstract: Along with improvement of technology in network and continuous expansion of network economy and network applications, the Internet has gradually become an indispensable part of the modern society. However, an endless stream of hacker attacks and network virus events make network security issues stand out. Therefore, network security has become a hot spot in computer network research and development. This paper aims at establishing a real-time detection and dynamic defense security system and makes an in-depth study of intrusion detection technology and defense decision-making technology. The strategy involved in finding the intrusion behavior since the fuzzy base contains the better group of rules. We have utilized an automated fuzzy rule generation strategy. An adaptive network intrusion detection and defense system model is established, and the architecture of the model is discussed in detail. The platform independence, good self-adaptability, expansibility, multi-level data analysis and dynamic defense decision-making are expounded. The experiment proves that the model proposed in this article has a good self-adaptability and open construction, and effectively combines the functions of intrusion detection and defense decision-making.

Keywords: Artificial intelligence, adaptive network, defense system, fuzzy rule

DOI: 10.3233/JIFS-189645

Journal: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8227-8235, 2021