Adversarial DDoS Attack Detection Based on Deep Learning and Open Set Recognition Techniques
The Internet has become an integral part of modern life,but it also faces many security risks,especially Distributed Denial of Service(DDoS)attacks.The use of artificial intelligence(AI)technology can address the challenges posed by DDoS attacks.It proposes a defense model based on CNN-Geo and Cycle GAN techniques,which includes an incremental learning module that is able to train unknown traffic and continuously improve the model's defense capability.This model can identify unknown attacks that deviate from the learning distribution,and the evaluated results show that its accuracy is more than 98.16%,which enhances the ability to detect and defend against the evolving DDoS attack strategies in real scenarios.
DDoSAIOpen set recognition(OSR)CNN-GeoCycle GANIncremental learning
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