Machine Learning Malware Detection For Android

During this past year up until now, the total of malware that targets the Android operating system has increased compared to other operating systems. Therefore, an application that used the android operating system must be analyzed to detect the malware before the malware causes serious damage. To a...

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Bibliographic Details
Main Author: Amir Muhammad Hafiz, Othman
Format: Undergraduates Project Papers
Language:English
Published: 2022
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/40874/
http://umpir.ump.edu.my/id/eprint/40874/1/CB20152.pdf
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author Amir Muhammad Hafiz, Othman
author_facet Amir Muhammad Hafiz, Othman
author_sort Amir Muhammad Hafiz, Othman
building UMP Institutional Repository
collection Online Access
description During this past year up until now, the total of malware that targets the Android operating system has increased compared to other operating systems. Therefore, an application that used the android operating system must be analyzed to detect the malware before the malware causes serious damage. To analyze the application, two types of analysis can be used which are static analysis and dynamic analysis. Static analysis is an analysis that is done by reviewing the codes diligently while dynamic analysis is an analysis that detects malware through observation. Even if both of the analysis was done successfully, however, an improvement needs to be done to detect the malware more accurately. With the technology arising now, there are many ways for the attacker to send malware to an Android smartphone user. Therefore, this research proposes a malware detection system using machine learning. This research objective is to detect the malware that attacks Android smartphones more accurately. The result of this research proves that the malware detection system is able to detect Android malware accurately.
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format Undergraduates Project Papers
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institution Universiti Malaysia Pahang
institution_category Local University
language English
last_indexed 2025-11-15T03:40:35Z
publishDate 2022
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spelling ump-408742024-04-03T07:39:52Z http://umpir.ump.edu.my/id/eprint/40874/ Machine Learning Malware Detection For Android Amir Muhammad Hafiz, Othman QA75 Electronic computers. Computer science During this past year up until now, the total of malware that targets the Android operating system has increased compared to other operating systems. Therefore, an application that used the android operating system must be analyzed to detect the malware before the malware causes serious damage. To analyze the application, two types of analysis can be used which are static analysis and dynamic analysis. Static analysis is an analysis that is done by reviewing the codes diligently while dynamic analysis is an analysis that detects malware through observation. Even if both of the analysis was done successfully, however, an improvement needs to be done to detect the malware more accurately. With the technology arising now, there are many ways for the attacker to send malware to an Android smartphone user. Therefore, this research proposes a malware detection system using machine learning. This research objective is to detect the malware that attacks Android smartphones more accurately. The result of this research proves that the malware detection system is able to detect Android malware accurately. 2022-10 Undergraduates Project Papers NonPeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/40874/1/CB20152.pdf Amir Muhammad Hafiz, Othman (2022) Machine Learning Malware Detection For Android. Faculty of Computing, Universiti Malaysia Pahang Al-Sultan Abdullah.
spellingShingle QA75 Electronic computers. Computer science
Amir Muhammad Hafiz, Othman
Machine Learning Malware Detection For Android
title Machine Learning Malware Detection For Android
title_full Machine Learning Malware Detection For Android
title_fullStr Machine Learning Malware Detection For Android
title_full_unstemmed Machine Learning Malware Detection For Android
title_short Machine Learning Malware Detection For Android
title_sort machine learning malware detection for android
topic QA75 Electronic computers. Computer science
url http://umpir.ump.edu.my/id/eprint/40874/
http://umpir.ump.edu.my/id/eprint/40874/1/CB20152.pdf