• Jayanthi

Currently protection is critical for computer networks because the internet is growing. Only the advent of the Internet of things does not guarantee the full protection of older technologies such as firewall, authorization and encryption. This also contributed to the creation of IDS, which tracks activities in computer networks to determine risks to information security. This paper introduced IDS with the aid of specific machine learning algorithms. Computer simulation technology improves the precision of real-time anomaly identification. This research focuses on the definition of support vector machines (SVMs) along with K-Nearest Neighbors (KNNs), that describe the performances of the program. A new approach is applied in this paper to avoid DoS (Denial of Service) assaults. In routers via the regular access list, marked KNN data that has a malicious IP address are disabled. A modern approach is applied in this paper in order to avoid DoS (Denial-of-Service) attacks. For routers, regular routers block the confidential KNN data that supplies malicious Domain names.

Computer security, Intrusion detection, KNN, Denial-of-Service, Computer simulation technology.

"Review on Network Intrusion Revealing and Prevention", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 1, page no.85-90, January-2019, Available :http://www.jetir.org/papers/JETIREU06017.pdf

"Review on Network Intrusion Revealing and Prevention", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 1, page no. pp85-90, January-2019, Available at : http://www.jetir.org/papers/JETIREU06017.pdf