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.
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Abstract
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.
Item Type: | Conference or Workshop Item (Full Paper) |
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Additional Information: | 4969/28865 |
Uncontrolled Keywords: | feature selection , machine learning , malware |
Subjects: | T Technology > T Technology (General) |
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): | Kulliyyah of Information and Communication Technology Kulliyyah of Information and Communication Technology |
Depositing User: | Nur' Aini Abu Bakar |
Date Deposited: | 14 Mar 2013 13:07 |
Last Modified: | 14 Mar 2013 13:07 |
URI: | http://irep.iium.edu.my/id/eprint/28865 |
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