With the rapid expansion of computer usage and computer network the security of the computer system has became very important. Every day new kind of attacks are being faced by industries. As the threat becomes a serious matter year by year, intrusion detection technologies are indispensable for network and computer security. A variety of intrusion detection approaches be present to resolve this severe issue but the main problem is performance. It is important to increase the detection rates and reduce false alarm rates in the area of intrusion detection. In order to detect the intrusion, various approaches have been developed and proposed over the last decade. In this paper, a detailed survey of intrusion detection based various techniques has been presented. Here, the techniques are classified as follows: i) papers related to Neural network ii) papers related to Support vector machine iii) papers related to K-means classifier iv) papers related to hybrid technique and v) paper related to other detection techniques. For comprehensive analysis, detection rate, time and false alarm rate from various research papers have been taken.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.