Intrusion Detection System Techniques : A Review

Abstract

Nowadays, Internet attacks are increasing rapidly. As a result, information security is a serious global concern among Information Technology users. Intrusion Detection System (IDS) is capable to detect unauthorized intrusions into computer systems and networks by looking for signatures of known attacks or deviations of normal activity. IDS is such as a detective control, the main function is to warn the user of any suspicious activity taking place. Active IDS research are still ongoing with remarkable techniques to detect attacks with significance accurate result. This paper deliver a brief overview on types of IDS and a types of techniques employed to detect intrusion.

Deep-learning-based Intrusion Detection with Enhanced Preprocesses

“…They can also be categorized into two types according to the technologies used for analysis: misuse intrusion detection (also named signature-based detection or rulebased detection) and anomaly intrusion detection. (3,4) Numerous studies have proposed the use of machine learning for intrusion detection. The classification performance of an intrusion detection system is strongly related to the feature extraction and selection results.…”

Gopalakrishnan, Shreevanth; Tuptuk, Nilufer; Hailes, Stephen; (2023) Machine Learning-based Intrusion Detection Systems: Deployment Guidelines for Industry

“…In this section, the different kinds of IDS are discussed, and where appropriate, the limitations of each of these models has also been presented. Based on where they are deployed, i.e., the type of data they see, IDS can be classified into the following [23], [24]: • Host-based (HIDS): This system monitors the host/device/endpoint it is deployed in. Its functions include monitoring and analysing internals of a host such as configuration files and application activity, and comparing them with previous "snapshots" where applicable; and monitoring the host's participation in the network, etc.…”