Malware detection through machine learning techniques

Malware attack is a never-ending cyber security issue. Since traditional approaches are less efficient in detecting newly appeared malware, researchers are applying machine learning methods. In this research we started by an overview of the domain and went over available malware datasets. Then we di...

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Main Authors: Amer, Ahmed, Abdul Aziz, Normaziah
Format: Article
Language:English
Published: The World Academy of Research in Science and Engineering 2019
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Online Access:http://irep.iium.edu.my/76535/1/76535_Malware%20detection%20through%20machine.pdf
http://irep.iium.edu.my/76535/
http://www.warse.org/IJATCSE/static/pdf/file/ijatcse82852019.pdf
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spelling my.iium.irep.765352019-12-26T00:35:57Z http://irep.iium.edu.my/76535/ Malware detection through machine learning techniques Amer, Ahmed Abdul Aziz, Normaziah QA75 Electronic computers. Computer science QA76 Computer software Malware attack is a never-ending cyber security issue. Since traditional approaches are less efficient in detecting newly appeared malware, researchers are applying machine learning methods. In this research we started by an overview of the domain and went over available malware datasets. Then we discussed disadvantages of traditional Anti-Malware methods and reviewed possible Machine Learning techniques used in this domain. A study on EMBER dataset has been made with an objective of improving the baseline Gradient Boosted Decision Tree model by optimizing its hyper-parameter and eliminating noisy features from the dataset. EMBER dataset consists of 1.1M observations of static features extracted from executable files. Our optimized model has achieved 99.38% accuracy with 0.004 false positive rate in 7 minutes running time. We conclude that Machine Learning techniques are practical to be applied as anti-malware solutions including for Zero-day attacks. The World Academy of Research in Science and Engineering 2019-10-01 Article PeerReviewed application/pdf en http://irep.iium.edu.my/76535/1/76535_Malware%20detection%20through%20machine.pdf Amer, Ahmed and Abdul Aziz, Normaziah (2019) Malware detection through machine learning techniques. International Journal of Advanced Trends in Computer Science and Engineering, 8 (5). pp. 2408-2413. ISSN 2278-3091 http://www.warse.org/IJATCSE/static/pdf/file/ijatcse82852019.pdf
institution Universiti Islam Antarabangsa Malaysia
building IIUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider International Islamic University Malaysia
content_source IIUM Repository (IREP)
url_provider http://irep.iium.edu.my/
language English
topic QA75 Electronic computers. Computer science
QA76 Computer software
spellingShingle QA75 Electronic computers. Computer science
QA76 Computer software
Amer, Ahmed
Abdul Aziz, Normaziah
Malware detection through machine learning techniques
description Malware attack is a never-ending cyber security issue. Since traditional approaches are less efficient in detecting newly appeared malware, researchers are applying machine learning methods. In this research we started by an overview of the domain and went over available malware datasets. Then we discussed disadvantages of traditional Anti-Malware methods and reviewed possible Machine Learning techniques used in this domain. A study on EMBER dataset has been made with an objective of improving the baseline Gradient Boosted Decision Tree model by optimizing its hyper-parameter and eliminating noisy features from the dataset. EMBER dataset consists of 1.1M observations of static features extracted from executable files. Our optimized model has achieved 99.38% accuracy with 0.004 false positive rate in 7 minutes running time. We conclude that Machine Learning techniques are practical to be applied as anti-malware solutions including for Zero-day attacks.
format Article
author Amer, Ahmed
Abdul Aziz, Normaziah
author_facet Amer, Ahmed
Abdul Aziz, Normaziah
author_sort Amer, Ahmed
title Malware detection through machine learning techniques
title_short Malware detection through machine learning techniques
title_full Malware detection through machine learning techniques
title_fullStr Malware detection through machine learning techniques
title_full_unstemmed Malware detection through machine learning techniques
title_sort malware detection through machine learning techniques
publisher The World Academy of Research in Science and Engineering
publishDate 2019
url http://irep.iium.edu.my/76535/1/76535_Malware%20detection%20through%20machine.pdf
http://irep.iium.edu.my/76535/
http://www.warse.org/IJATCSE/static/pdf/file/ijatcse82852019.pdf
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score 13.144533