Unknown Cyber Threat Discovery Empowered by Genetic Evolution Without Prior Knowledge

With the continuous development of cyber-attack technologies, attackers increasingly exploit zero-day vulnerabilities or leverage emerging techniques to launch sophisticated attacks, resulting in the persistent emergence of unknown cyber-attacks. However, traditional DL-based cyber-attack detection...

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Veröffentlicht in:	IEEE transactions on information forensics and security Jg. 20; S. 9552 - 9567
Hauptverfasser:	Fang, Wenbo, He, Junjiang, Li, Wenshan, Ma, Wengang, Zhang, Linlin, Lan, Xiaolong, Yang, Geying, Chen, Jiangchuan, Li, Tao
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	IEEE 2025
Schlagworte:	Autoencoders Classification algorithms convolutional autoencoder Cyberattack Evolution (biology) Generative adversarial networks genetic evolution Genetics global attention local attention Optimization Support vector machines Technological innovation Training Unknown cyber-attack
ISSN:	1556-6013, 1556-6021
Online-Zugang:	Volltext
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