Challenges in high accuracy of malware detection

Malware is a threat to the computer users regardless which operating systems and hardware platforms that they are using. Microsoft Windows is the most popular operating system and the popularity also make it the most favourite platform to be attacked by the adversaries. Current detection for Windows...

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Main Authors: Ahmad Zabidi, Muhammad Najmi, Maarof, Mohd Aizaini, Zainal, Anazida
Format: Proceeding Paper
Language:English
Published: 2012
Subjects:
Online Access:http://irep.iium.edu.my/28865/
http://irep.iium.edu.my/28865/1/Challenges_in_high_accuracy.pdf
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author Ahmad Zabidi, Muhammad Najmi
Maarof, Mohd Aizaini
Zainal, Anazida
author_facet Ahmad Zabidi, Muhammad Najmi
Maarof, Mohd Aizaini
Zainal, Anazida
author_sort Ahmad Zabidi, Muhammad Najmi
building IIUM Repository
collection Online Access
description Malware is a threat to the computer users regardless which operating systems and hardware platforms that they are using. Microsoft Windows is the most popular operating system and the popularity also make it the most favourite platform to be attacked by the adversaries. Current detection for Windows relies on the signature based detection which is fairly fast although suffers undetected binaries. Here, we propose a method to increase the detection rate of malware by manipulating machine learning methods. Our focus is on the Microsoft Windows binaries.
first_indexed 2025-11-14T15:27:06Z
format Proceeding Paper
id iium-28865
institution International Islamic University Malaysia
institution_category Local University
language English
last_indexed 2025-11-14T15:27:06Z
publishDate 2012
recordtype eprints
repository_type Digital Repository
spelling iium-288652013-03-14T05:07:58Z http://irep.iium.edu.my/28865/ Challenges in high accuracy of malware detection Ahmad Zabidi, Muhammad Najmi Maarof, Mohd Aizaini Zainal, Anazida T Technology (General) Malware is a threat to the computer users regardless which operating systems and hardware platforms that they are using. Microsoft Windows is the most popular operating system and the popularity also make it the most favourite platform to be attacked by the adversaries. Current detection for Windows relies on the signature based detection which is fairly fast although suffers undetected binaries. Here, we propose a method to increase the detection rate of malware by manipulating machine learning methods. Our focus is on the Microsoft Windows binaries. 2012 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/28865/1/Challenges_in_high_accuracy.pdf Ahmad Zabidi, Muhammad Najmi and Maarof, Mohd Aizaini and Zainal, Anazida (2012) Challenges in high accuracy of malware detection. In: 2012 IEEE Control and System Graduate Research Colloquium (ICSGRC 2012), 16-17 July 2012, Shah Alam, Selangor. http://ieeexplore.ieee.org/xpl/articleDetails.jsp?reload=true&arnumber=6287147
spellingShingle T Technology (General)
Ahmad Zabidi, Muhammad Najmi
Maarof, Mohd Aizaini
Zainal, Anazida
Challenges in high accuracy of malware detection
title Challenges in high accuracy of malware detection
title_full Challenges in high accuracy of malware detection
title_fullStr Challenges in high accuracy of malware detection
title_full_unstemmed Challenges in high accuracy of malware detection
title_short Challenges in high accuracy of malware detection
title_sort challenges in high accuracy of malware detection
topic T Technology (General)
url http://irep.iium.edu.my/28865/
http://irep.iium.edu.my/28865/
http://irep.iium.edu.my/28865/1/Challenges_in_high_accuracy.pdf