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Reseach Article

Intrusion Detection in Dos Attacks

by P.Rajapandian, Dr.K.Alagarsamy
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 15 - Number 8
Year of Publication: 2011
Authors: P.Rajapandian, Dr.K.Alagarsamy
10.5120/1967-2634

P.Rajapandian, Dr.K.Alagarsamy . Intrusion Detection in Dos Attacks. International Journal of Computer Applications. 15, 8 ( February 2011), 33-37. DOI=10.5120/1967-2634

@article{ 10.5120/1967-2634,
author = { P.Rajapandian, Dr.K.Alagarsamy },
title = { Intrusion Detection in Dos Attacks },
journal = { International Journal of Computer Applications },
issue_date = { February 2011 },
volume = { 15 },
number = { 8 },
month = { February },
year = { 2011 },
issn = { 0975-8887 },
pages = { 33-37 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume15/number8/1967-2634/ },
doi = { 10.5120/1967-2634 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:03:36.719888+05:30
%A P.Rajapandian
%A Dr.K.Alagarsamy
%T Intrusion Detection in Dos Attacks
%J International Journal of Computer Applications
%@ 0975-8887
%V 15
%N 8
%P 33-37
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Different signature or misuse based intrusion detection techniques; anomaly detection is accomplished of detecting novel attacks. However, the use of anomaly detection in practice is vulnerable by a high rate of false alarms. Pattern based techniques have been shown to make a low rate of false alarms, but are not as efficient as anomaly detection in detecting novel attacks, particularly when it comes to network probing and Denial-Of-Service (DOS) attacks. In this paper we find a new approach that merge pattern-based and anomaly-based intrusion detection, mitigating the weak point of the two approaches while increasing their strengths. Our approach begins with network protocols, and expands these state machines with information about statistics that need to be maintained to detect anomalies.

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Index Terms

Computer Science
Information Sciences

Keywords

Intrusion detection Anomaly detection Network monitoring Denial-Of-Service Misuse detection