Dr. Zhenjiang Liu Profile

Dr. Zhenjiang Liu

at Tongji Univ

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Proceedings Article | 14 January 2023 Paper

Detecting DDoS issues under 5G with ResNet

Zhenjiang Liu

Proceedings Volume 12510, 1251013 (2023) https://doi.org/10.1117/12.2657423

KEYWORDS: Data modeling, Data conversion, Network security, Binary data, Internet, Floods, Performance modeling, Image classification, X-rays, X-ray imaging

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The operation of the network is often accompanied by network attacks, and as the network begins to gradually enter the 5G era, the intensity of network attacks and attacks are also rising significantly, of which Distributed Denial of Service (DDoS), as the mainstream attack of network attacks, has a very high attack intensity and attack frequency, and the traditional detection system is unable to detect the complex DDoS attacks. However, when the detection scheme is combined with artificial intelligence, it becomes efficient and reliable. Over the years, the detection of DDoS attacks has achieved very good results. However, in the face of the advent of the 5G era, higher requirements are put forward for detecting DDoS attacks. Given the good potential and performance of Convolutional Neural Networks (CNN) in classifying images, this work proposes a method to convert network traffic into images and apply the ResNet model for training on the converted data. The work sacrifice some of the accuracy on binary classification, which drops to 99.6% but improve 2% on multivariate classification over previous work to 89%.

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