TRAFFIC DETECTION OF TRANSMISSION OF BOTNET THREAT USING BP NEURAL NETWORK

Abstract

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 while bringing convenience. The most serious threat to network security faced by the Internet is a variety of malicious network attacks on the carrier of botnets. 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 alarm rate. The results showed that it had high detection rate and low false alarm rate, which indicated that the BP neural network had a good performance in detecting the traffic of botnet threat transmission.