Multi-Traffic Features Network Intrusion Detection Algorithm Based on C4.5
Jingwen Zhou, Xinnan Jiang, Chang Liu, Jing Zhang, Lingling Liao, Jiazhong Lu · 2021 18th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP) · 2021
With more and more network attacks on the Internet, this article uses the C4.5 decision tree classification algorithm to detect 7 types of network attacks from the perspective of network traffic. Firstly, the data is preprocessed, then extract 62 features, finally use our proposed C4.5 divided algorithm for traffic detection. This experiment uses the public data set CSE-CIC-IDS2018 for verification. The experimental results show that the method in this article can effectively detect different types of cyber attacks. The accuracy rate can reach 96.7%, and the false positive rate is only 4.5%.