Editor/Reviewer loginFrequency : 12 issues per year
Subject : Computer Applications and Technology
ISSN : 2319–8656 (Online)
IJCATR Volume 5 Issue 9
A Study of Intrusion Detection System Methods in Computer Networks
Mohammad Hossein Karamzadeh Reza Sheibani
10.7753/IJCATR0509.1001
keywords : Intrusion Detection, Normal Network, Genetic Algorithm, Computer Networks
Intrusion detection system (IDS) is an application system monitoring the network for malicious or intrusive activity. In these systems, malicious or intrusive activities intrusion can be detected by using information like port scanning and detecting unusual traffic, and then they can be reported to the network. Since intrusion detection systems do not involve predefined detection power and intrusion detection, they require being intelligent. In this case, systems have the capability of learning. They can analyze packages entering the network, and detect normal and unusual users. The common intelligent methods are neural networks, fuzzy logic, data mining techniques, and genetic algorithms. In this research, the purpose is to study various intelligent methods.
@artical{m592016ijcatr05091001,
Title = "A Study of Intrusion Detection System Methods in Computer Networks",
Journal ="International Journal of Computer Applications Technology and Research(IJCATR)",
Volume = "5",
Issue ="9",
Pages ="556 - 560",
Year = "2016",
Authors ="Mohammad Hossein Karamzadeh
Reza Sheibani"}
In this research examined data mining is banking risk.
Data mining, decision trees and neural network techniques have been investigated.
In the simulation, a performance evaluation of the algorithm is carried out.
In this research the criteria used to assess the accuracy.