Abstract:
This thesis is on “Comparative Analysis of Intrusion Prevention System.”. The main domain of this thesis is network security. Intrusion Prevention System is a well-known and
important part of network security. Intrusion Prevention System provides critical infrastructures security by preventing intrusions in the network and computer systems. The aim of this thesis is to learn more about Intrusion Prevention System, know their
implementation procedures, knowledge gathering on deep level packet inspection and find
out the performance of most common open Intrusion Prevention Systems. In this study two most common Intrusion Prevention System (Snort and Suricata) is used to learn and
experiment the performance on latest intrusion dataset named CICIDS2017. Performance
are measured based on the CPU Utilization, Packet Processing speed, and on detection and prevention accuracy rate. Detection and prevention accuracy is measured using data mining techniques where different Machine Learning algorithms has been used.
