Random Forests for Online Intrusion Detection in Computer Networks
- 1 Instituto Federal de Mato Grosso do Sul, Brazil
- 2 Universidade Federal de Lavras, Brazil
This study proposes a methodology to build an Online Network Intrusion Detection System by using the Computational Intelligence technique called Random Forests and an API to preprocess the network packets. The experiments were carried out from two network traffic databases: The ISCX (i); and a test database (ii) created with the proposed API in our own network environment. The results obtained with the Random Forests technique show accuracy rates around 98%, bringing significant advances in the area of Intrusion Detection and affirming the high efficiency of the use of the technique to solve problems of intrusion detection in real network environments.
Copyright: © 2021 Heitor Scalco Neto, Wilian Soares Lacerda and Rafael Verão Françozo. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
- 464 Views
- 275 Downloads
- 0 Citations
- Intrusion Detection Systems
- Computer Networks
- Computational Intelligence
- Random Forests