Low-Rate Denial-of-Service detection based on Convolutional Neural Network

Abstract

Low-Rate Denial-of-Service (LDoS) is an attack method often faced in environments with low computing power. In this environment, attackers can hide attack packets in sufficiently low-rate data streams to escape detection has greatly increased the difficulty of detection, which makes traditional methods unable to extract features smoothly due to insufficient data and cannot accurately identify attackers. In order to improve this problem, this article uses artificial intelligence convolutional neural networks (CNN) to achieve stronger global search, the experimental results show that the method proposed in this article can effectively detect LDoS attacks.