Anti-Obfuscation Techniques: Recent Analysis of Malware Detection

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F22%3A50019519" target="_blank" >RIV/62690094:18450/22:50019519 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.3233/FAIA220249" target="_blank" >http://dx.doi.org/10.3233/FAIA220249</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3233/FAIA220249" target="_blank" >10.3233/FAIA220249</a>

Result language

angličtina

Original language name

Anti-Obfuscation Techniques: Recent Analysis of Malware Detection

Original language description

One of the challenging issues in detecting the malware is that modern stealthy malware prefers to stay hidden during their attacks on our devices and be obfuscated. They can evade antivirus scanners or other malware analysis tools and might attempt to thwart modern detection, including altering the file attributes or performing the action under the pretense of authorized services. Therefore, it&apos;s crucial to understand and analyze how malware implements obfuscation techniques to curb these concerns. This paper is dedicated to presenting an analysis of anti-obfuscation techniques for malware detection. Furthermore, an empirical analysis of the performance evaluation of malware detection using machine learning algorithms and the obfuscation techniques was conducted to address the associated issues that might help researchers plan and generate an efficient algorithm for malware detection. © 2022 The authors and IOS Press. All rights reserved.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2022

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Frontiers in Artificial Intelligence and Applications

ISBN

978-1-64368-316-4

ISSN

0922-6389

e-ISSN

1535-6698

Number of pages

12

Pages from-to

181-192

Publisher name

IOS Press BV

Place of publication

Amsterdam

Event location

Kitakyushu

Event date

Sep 20, 2022

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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