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Detection and Classification of Intrusions using Fusion Probability of HMM

by Hemlata Sukhwani, Shwaita Kodesia, Sanjay Sharma
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 103 - Number 12
Year of Publication: 2014
Authors: Hemlata Sukhwani, Shwaita Kodesia, Sanjay Sharma
10.5120/18127-9213

Hemlata Sukhwani, Shwaita Kodesia, Sanjay Sharma . Detection and Classification of Intrusions using Fusion Probability of HMM. International Journal of Computer Applications. 103, 12 ( October 2014), 26-30. DOI=10.5120/18127-9213

@article{ 10.5120/18127-9213,
author = { Hemlata Sukhwani, Shwaita Kodesia, Sanjay Sharma },
title = { Detection and Classification of Intrusions using Fusion Probability of HMM },
journal = { International Journal of Computer Applications },
issue_date = { October 2014 },
volume = { 103 },
number = { 12 },
month = { October },
year = { 2014 },
issn = { 0975-8887 },
pages = { 26-30 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume103/number12/18127-9213/ },
doi = { 10.5120/18127-9213 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:34:23.163771+05:30
%A Hemlata Sukhwani
%A Shwaita Kodesia
%A Sanjay Sharma
%T Detection and Classification of Intrusions using Fusion Probability of HMM
%J International Journal of Computer Applications
%@ 0975-8887
%V 103
%N 12
%P 26-30
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Intrusion detection system is a technique of identifying unwanted packets that creates harm in the network; hence various IDS are implemented for the security of network traffic flow. Here in this paper an efficient technique of identifying intrusions is implemented using hidden markov model and then classification of these intrusions is done. The methodology sis applied on KDDCup 99 dataset where the dataset is first clustered using K-means algorithms and then a number of attributes is selected which are used for the detection of intrusion is passed to the HMM, after calculating probability from each of the states, these probabilities are fused to get the resultant final probability and also overall probability is calculated from dataset on the basis of which intrusions are classified as low, medium or high.

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Index Terms

Computer Science
Information Sciences

Keywords

IDS Anomaly HMM Behavioral Distance

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