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...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
2011
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| Subjects: | |
| Online Access: | 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 |
| Summary: | 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.
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