Author(s)

Mingyuan Xin, Yong Wang and lin Fan

Corresponding Author

Mingyuan Xin

Abstract

In order to solve the problem of high false alarm rate and low false alarm rate in massive network data intrusion detection, this paper proposes an intrusion detection model based on convolution neural network, which can improve the classification accuracy by selecting convolution core and data to extract local feature correlation features.

Keywords

In-Depth learning, Intrusion detection, Artificial intelligence