The security of computer networks is crucial in today’s computer systems. A number of software technologies are now being developed in order to impose high levels of protection against harmful attacks. Because of their potential to detect and prevent assaults by malicious network users, intrusion detection systems have recently become a hot research issue. This article discusses various recent techniques such as anomaly, signature, open source IDS such as SNORT, machine learning, and edge assisted technologies in detail, along with the advantages and disadvantages of the deployed system. The tools used, datasets, performance metrics, and the accuracy of the methodologies are compared, and it gives a clear view of further advancements in computer networks. Based on the studies, it can be said that machine learning algorithms work better than other traditional methods and make security better.