1. Traffic detection of transmission of botnet threat using BP neural network
- Creator:
- Li, Xingguo and Wang, Junfeng
- Format:
- bez média and svazek
- Type:
- model:article and TEXT
- Subject:
- botnet, BP neural network, traffic, and detection
- Language:
- English
- Description:
- With the gradual improvement of the telecommunication infrastructure in China, the Internet and other new technologies have been frequently used. The Internet technology also brings many network security threats, for example, botnet, while bringing convenience. Botnet is a network formed between hosts controlled by malicious code. One of the most serious threat to network security faced by the Internet is a variety of malicious network attacks on the carrier of botnet. Back propagation (BP) neural network is proposed to detect botnet threat transmission. In this study, a botnet detection model was established using BP neural network system. BP neural network classifier could identify the botnet traffic and normal traffic. Moreover a test was carried out to detect botnet traffic using BP neural network; the performance of the BP neural network classifier was evaluated by the detection rate and false positive rate. The results showed that it had high detection rate and low false positive rate, which indicated that the BP neural network had a good performance in detecting the traffic of botnet threat transmission.
- Rights:
- http://creativecommons.org/publicdomain/mark/1.0/ and policy:public