Comparative analysis of Snort and Suricata intrusion detection systems

Different approaches to the organization of open-source intrusion detection systems are considered. In this context, network intrusion detection systems become an important element of network security, providing reliable protection against potential threats to the integrity, confidentiality, and availability of data in the network. Many network intrusion detection systems have been proposed in the literature, but Snort and Suricata are the best known and most common among open-source solutions. The paper compares the performance of these two network intrusion detection systems. A quantitative study was performed in a virtualized network environment to evaluate the performance of each system in terms of accuracy, memory and central processing unit usage, and packet processing speed, and packet loss rate. The study found that Snort and Suricata perform well but have some limitations that need to be addressed. During testing, Snort’s intrusion detection system exhibited lower detection latency. At the same time, Suricata demonstrates higher detection accuracy due to a more comprehensive set of community-supplied rules. However, the higher processing requirements of Suricata caused this system to reach its operational limits faster than Snort.