Performance and Accuracy Assessment of Detecting Network Intrusions with eSOM-Based Techniques

In this study are provided results about performance evaluation of Emergent Self-Organizing Map-based Intrusion Detection System in simulated wireless network environment. The experiment included detection of various network intrusions, including DoS, Probe, R2L, and U2R attacks. The results show that DoS (95%) and Probe (88%) attacks had the higher detection rates, while R2L (75%) and U2R (70%) attacks had the lower detection rates. The evaluated system demonstrated a low false positive rate of 5% and quick response times for overt attacks (2 seconds), though response times increased for covert attacks (4 seconds). During the experiment, the amount of used calculation resources was considerably high - the average CPU utilization was 70% and 80%, respectively. The results show that in order to effectively use this type of Intrusion Detection System for real company network security, there is need for further optimization.