(untitled) (Latin-American Journal of Computing, 2020)
The purpose of this research work is to evaluate the functionality of the intrusion detection systems (IDS) based on Open Source platforms using the anomalies detection technique, defining several concepts about intrusion detection systems. For the evaluation of the IDS a methodology based on the application and quasi-experimental research was used, considering the existing knowledge and the implementation of the cases of: learning, simulation of attacks and application by means of virtual scenarios, on which they were installed the Snort, Suricata and Bro IDS and the different Benchmark tools. The correlation of the alerts issued by both Snort and Suricata using the anomaly detection technique based on statistical data, allowed to determine the true positives (TP) for the effective alerts and the false negatives (FN) for the anomalies.