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Comparative Analysis of Feature Extraction Methods of Malware Detection
by
Smita Ranveer,
Swapnaja Hiray
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 120 - Number 5 |
| Year of Publication: 2015 |
| Authors: Smita Ranveer, Swapnaja Hiray |
10.5120/21220-3960
|
Smita Ranveer, Swapnaja Hiray . Comparative Analysis of Feature Extraction Methods of Malware Detection. International Journal of Computer Applications. 120, 5 ( June 2015), 1-7. DOI=10.5120/21220-3960
@article{
10.5120/21220-3960,
author = {
Smita Ranveer,
Swapnaja Hiray
},
title = { Comparative Analysis of Feature Extraction Methods of Malware Detection },
journal = {
International Journal of Computer Applications
},
issue_date = { June 2015 },
volume = { 120 },
number = { 5 },
month = { June },
year = { 2015 },
issn = { 0975-8887 },
pages = {
1-7
},
numpages = {9},
url = {
https://ijcaonline.org/archives/volume120/number5/21220-3960/
},
doi = { 10.5120/21220-3960 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:05:25.025205+05:30
%A Smita Ranveer
%A Swapnaja Hiray
%T Comparative Analysis of Feature Extraction Methods of Malware Detection
%J International Journal of Computer Applications
%@ 0975-8887
%V 120
%N 5
%P 1-7
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract
Recent years have encountered massive growth in malwares which poses a severe threat to modern computers and internet security. Existing malware detection systems are confronting with unknown malware variants. Recently developed malware detection systems investigated that the diverse forms of malware exhibit similar patterns in their structure with minor variations. Hence, it is required to discriminate the types of features extracted for detecting malwares. So that potential of malware detection system can be leveraged to combat with unfamiliar malwares. We mainly focus on the categorization of features based on malware analysis. This paper highlights general framework of malware detection system and pinpoints strengths and weaknesses of each method. Finally we presented overview of performance of present malware detection systems based on features.
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Index Terms
Computer Science
Information Sciences
Keywords