An Intelligent Network Intrusion Detector Using Deep Learning Model
Zheming Zhang, Yunjian Li, Aoran Shen, Jiajun Hu · 2022
Network intrusion detection is a technology that detects and responds to behaviors that endanger computer security, such as collecting vulnerability information, denying access, and gaining system control beyond the legal scope. The timely detection and control of these destructive behaviors play a vital role in the overall security of the entire computer system and network environment. This paper proposes a DNN-based network intrusion prediction model based on a set of intrusion datasets simulated in a military network environment. Experiments show that the proposed method has better prediction performance than models based on GaussianNB, Decision Tree and Logistic Regression.