Classification of Computer Network Users with Convolutional Neural Networks

Abstract

Automatic detection of abnormal behaviour of computer network users is a desirable and hard to achieve feature. We show that convolutional neural networks can classify users in local computer networks based on features of web pages which were requested by a user (e.g. URL address, URL category, the day of week or time when the web page was visited). We demonstrate our approach on data collected from a firewall over an eight-month period. This network traffic meta-data allowed to achieve satisfactory classification accuracy on unseen, future network traffic data.