A DDOS attack detection method based on recurrent neural network

Yue Wu

doi:10.1117/12.3013363

29 November 2023 A DDOS attack detection method based on recurrent neural network

Yue Wu

Proceedings Volume 12937, International Conference on Internet of Things and Machine Learning (IoTML 2023); 1293706 (2023) https://doi.org/10.1117/12.3013363
Event: International Conference on Internet of Things and Machine Learning (IoTML 2023), 2023, Singapore, Singapore

Abstract

With the rapid development of cloud computing and mobile Internet, there have been a variety of network attacks, among which distributed denial of service (DDoS) is one of the most fatal attacks. Traditional machine learning detection methods face serious challenges. This paper proposes a method for identifying DDoS attacks based on RNNs. Taking Recurrent Neural Network (RNN) as the research and improvement object, long short-term memory, bidirectional recurrent neural network and other technologies are used. Experiments on the public dataset indicate that the accuracy of the model can reach 99.97%, which is better than the traditional machine learning model and achieves a good recognition effect

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yue Wu "A DDOS attack detection method based on recurrent neural network", Proc. SPIE 12937, International Conference on Internet of Things and Machine Learning (IoTML 2023), 1293706 (29 November 2023); https://doi.org/10.1117/12.3013363

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