基于GRU的无线局域网DOS攻击检测方法

s an important way to connect to the Internet, WLAN has changed the situation of Internet communication only relying on wired networking technology. With the rapid development of WLAN technology and the large-scale popularization of wireless terminal equipment, WLAN has been widely used in campus, subway, shopping malls and other public places with large traffic. Among them, DOS (denial of service) attack in WLAN is a more common way of wireless attack. Its attack method is relatively simple and difficult to prevent, which has seriously restricted the further development of WLAN. Because there are many types of wireless DoS attacks, this paper proposes a wireless LAN DoS attack detection method based on Gru (gated recurrent unit) neural network. Firstly, different types of DoS attacks are reproduced in the experimental environment to find out the frame types that can distinguish different types of DoS attacks. Then the prediction model of wireless DoS attack is generated by Gru neural network, and the prediction model is evaluated by the accuracy, recall and F value commonly used in machine learning. The model can be used to detect wireless DoS attack after passing the evaluation.