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Reseach Article

Overview of Malware Analysis and Detection

Published on July 2015 by Aziz Makandar, Anita Patrot
National Conference on Knowledge, Innovation in Technology and Engineering (NCKITE 2015)
Foundation of Computer Science USA
NCKITE2015 - Number 1
July 2015
Authors: Aziz Makandar, Anita Patrot
78448ce3-1c29-4842-a077-ab90c191a6dc

Aziz Makandar, Anita Patrot . Overview of Malware Analysis and Detection. National Conference on Knowledge, Innovation in Technology and Engineering (NCKITE 2015). NCKITE2015, 1 (July 2015), 35-40.

@article{
author = { Aziz Makandar, Anita Patrot },
title = { Overview of Malware Analysis and Detection },
journal = { National Conference on Knowledge, Innovation in Technology and Engineering (NCKITE 2015) },
issue_date = { July 2015 },
volume = { NCKITE2015 },
number = { 1 },
month = { July },
year = { 2015 },
issn = 0975-8887,
pages = { 35-40 },
numpages = 6,
url = { /proceedings/nckite2015/number1/21480-2649/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Knowledge, Innovation in Technology and Engineering (NCKITE 2015)
%A Aziz Makandar
%A Anita Patrot
%T Overview of Malware Analysis and Detection
%J National Conference on Knowledge, Innovation in Technology and Engineering (NCKITE 2015)
%@ 0975-8887
%V NCKITE2015
%N 1
%P 35-40
%D 2015
%I International Journal of Computer Applications
Abstract

Several methods have been devised to smooth the progress of malware analysis and one of them is through visualization techniques. Visualization technique is a basic method which is used to visualize the features of malware or variants. This field focuses on features of individual variants and also helpful to the researchers to identify malware easily. The behaviors of malware are identified by variants such as encrypted, polymorphic, metamorphic, and obfuscated which have the ability to change their code as they propagate. In this paper various types of malware is discusses briefly with their categorization of malware families. Techniques of detection and classification of malware motivated especially on behaviors of malware samples which are similar in texture and some extent through this we can classify the malware data. This paper provides an overview of existing malware detection techniques.

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Index Terms

Computer Science
Information Sciences

Keywords

Malware Static Analysis Dynamic Analysis Detection Classification Visualization.