Ensemble based categorization and adaptive model for malware detection
Malware, a term which was derived from two words; malicious software has caused many problem to the computer users throughout the world. Previously was known as many names; trojan, virus, worms, dialers and many others, thid potientially unwanted software simply labeled as malware. Malware is a...
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iium-158602012-07-26T01:49:46Z http://irep.iium.edu.my/15860/ Ensemble based categorization and adaptive model for malware detection Ahmad Zabidi, Muhammad Najmi Maarof, Mohd Aizaini Zainal, Anazida QA75 Electronic computers. Computer science Malware, a term which was derived from two words; malicious software has caused many problem to the computer users throughout the world. Previously was known as many names; trojan, virus, worms, dialers and many others, thid potientially unwanted software simply labeled as malware. Malware is a software, which works as any other benigh software, but was designed to accomplish the goal of its writers. It was written to exploit the vulnerability of the target victim’s operating system or application. Previously was a primitive and easy to detect, it evolves to a sophisticated and professionally written piece of software. Current malware detection method involved string search algorithm which based on the pattern detection. This may include the use of signature based method. In this paper, we propose an ensemble categorization by using ensemble classification and clustering together with adaptive learning model. 2011-12 Article PeerReviewed application/pdf en http://irep.iium.edu.my/15860/1/Ensemble_Based_Categorization_and_Adaptive_Model_for_Malware_Detection.pdf Ahmad Zabidi, Muhammad Najmi and Maarof, Mohd Aizaini and Zainal, Anazida (2011) Ensemble based categorization and adaptive model for malware detection. 2011 7th International Conference on Information Assurance and Security (IAS), 978-1-. pp. 80-85. http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6122799&tag=1 |
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QA75 Electronic computers. Computer science |
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QA75 Electronic computers. Computer science Ahmad Zabidi, Muhammad Najmi Maarof, Mohd Aizaini Zainal, Anazida Ensemble based categorization and adaptive model for malware detection |
description |
Malware, a term which was derived from two
words; malicious software has caused many problem to the
computer users throughout the world. Previously was known
as many names; trojan, virus, worms, dialers and many others,
thid potientially unwanted software simply labeled as malware.
Malware is a software, which works as any other benigh
software, but was designed to accomplish the goal of its writers.
It was written to exploit the vulnerability of the target victim’s
operating system or application. Previously was a primitive and
easy to detect, it evolves to a sophisticated and professionally
written piece of software. Current malware detection method
involved string search algorithm which based on the pattern
detection. This may include the use of signature based method.
In this paper, we propose an ensemble categorization by using
ensemble classification and clustering together with adaptive
learning model.
|
format |
Article |
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 |
title |
Ensemble based categorization and adaptive model for malware detection |
title_short |
Ensemble based categorization and adaptive model for malware detection |
title_full |
Ensemble based categorization and adaptive model for malware detection |
title_fullStr |
Ensemble based categorization and adaptive model for malware detection |
title_full_unstemmed |
Ensemble based categorization and adaptive model for malware detection |
title_sort |
ensemble based categorization and adaptive model for malware detection |
publishDate |
2011 |
url |
http://irep.iium.edu.my/15860/ http://irep.iium.edu.my/15860/ http://irep.iium.edu.my/15860/1/Ensemble_Based_Categorization_and_Adaptive_Model_for_Malware_Detection.pdf |
first_indexed |
2023-09-18T20:24:45Z |
last_indexed |
2023-09-18T20:24:45Z |
_version_ |
1777408342438707200 |