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Malware Detection In Android Using Machine Learning

In an era that is increasingly fast with advanced technology, smartphones are a priority and a necessity for everyone. These gadgets are developing every day towards more advanced and appropriate ways of use. However, security is one of the causes of concern for many smartphone users. Safety is an i...

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Main Author: Muhammad Hazriq Akmal, Zairol
Format: Undergraduates Project Papers
Language:English
Published: 2023
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://umpir.ump.edu.my/id/eprint/40708/1/CA20144.pdf
http://umpir.ump.edu.my/id/eprint/40708/
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spelling my.ump.umpir.407082024-03-18T08:04:28Z http://umpir.ump.edu.my/id/eprint/40708/ Malware Detection In Android Using Machine Learning Muhammad Hazriq Akmal, Zairol QA75 Electronic computers. Computer science In an era that is increasingly fast with advanced technology, smartphones are a priority and a necessity for everyone. These gadgets are developing every day towards more advanced and appropriate ways of use. However, security is one of the causes of concern for many smartphone users. Safety is an important aspect that is highly regarded and taken seriously by some parties, and if this safety issue is taken for granted and not taken care of, it will cause problems to the people surrounding. Just like the security issue of smartphone users, which is now increasingly prevalent with one of the biggest threats to all gadgets, which is the malware issue. Studies have shown that there is an increase from year to year regarding malware that is more focused on attacking and damaging the victim's smartphone, especially for Android users. Many Android users have been affected by this malware problem and various solutions have been implemented. This study aims to examine the ways and methods of detecting malware that has attacked the Android operating system, and suggest the detection of a malware detection system by using machine learning techniques. The results show that machine learning is a more promising approach with 90% accuracy in experiments that have been conducted for machine learning methods for higher malware detection and prove that this malware detection system can detect Android malware more efficiently. 2023-06 Undergraduates Project Papers NonPeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/40708/1/CA20144.pdf Muhammad Hazriq Akmal, Zairol (2023) Malware Detection In Android Using Machine Learning. Faculty of Computing, Universiti Malaysia Pahang Al-Sultan Abdullah.
institution Universiti Malaysia Pahang Al-Sultan Abdullah
building UMPSA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang Al-Sultan Abdullah
content_source UMPSA Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Muhammad Hazriq Akmal, Zairol
Malware Detection In Android Using Machine Learning
description In an era that is increasingly fast with advanced technology, smartphones are a priority and a necessity for everyone. These gadgets are developing every day towards more advanced and appropriate ways of use. However, security is one of the causes of concern for many smartphone users. Safety is an important aspect that is highly regarded and taken seriously by some parties, and if this safety issue is taken for granted and not taken care of, it will cause problems to the people surrounding. Just like the security issue of smartphone users, which is now increasingly prevalent with one of the biggest threats to all gadgets, which is the malware issue. Studies have shown that there is an increase from year to year regarding malware that is more focused on attacking and damaging the victim's smartphone, especially for Android users. Many Android users have been affected by this malware problem and various solutions have been implemented. This study aims to examine the ways and methods of detecting malware that has attacked the Android operating system, and suggest the detection of a malware detection system by using machine learning techniques. The results show that machine learning is a more promising approach with 90% accuracy in experiments that have been conducted for machine learning methods for higher malware detection and prove that this malware detection system can detect Android malware more efficiently.
format Undergraduates Project Papers
author Muhammad Hazriq Akmal, Zairol
author_facet Muhammad Hazriq Akmal, Zairol
author_sort Muhammad Hazriq Akmal, Zairol
title Malware Detection In Android Using Machine Learning
title_short Malware Detection In Android Using Machine Learning
title_full Malware Detection In Android Using Machine Learning
title_fullStr Malware Detection In Android Using Machine Learning
title_full_unstemmed Malware Detection In Android Using Machine Learning
title_sort malware detection in android using machine learning
publishDate 2023
url http://umpir.ump.edu.my/id/eprint/40708/1/CA20144.pdf
http://umpir.ump.edu.my/id/eprint/40708/
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score 13.235362

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