Malware detection application for android using machine learning
Mobile phones especially smartphone is now an essential item in today’s society, granting user’s ability to perform tasks and brining convenience to its user. While IOS popularity is constantly growing, android still commands much of the market share and thus has been seen as a lucrative market f...
| Main Author: | |
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| Other Authors: | |
| Format: | Final Year Project (FYP) |
| Language: | English |
| Published: |
2019
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| Subjects: | |
| Online Access: | http://hdl.handle.net/10356/77225 |
| _version_ | 1826122992416980992 |
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| author | Loh, Jing Kai |
| author2 | Liu Yang |
| author_facet | Liu Yang Loh, Jing Kai |
| author_sort | Loh, Jing Kai |
| collection | NTU |
| description | Mobile phones especially smartphone is now an essential item in today’s society, granting user’s
ability to perform tasks and brining convenience to its user. While IOS popularity is constantly
growing, android still commands much of the market share and thus has been seen as a lucrative
market for malicious actors to benefit off this huge market. Although a variety of methods exist to
protect users from these malicious actors, those solutions tend to have negative drawbacks to them.
Thus, new way to be able to detect these malwares is needed.
In this project, the focus will be on the development of malware detection tool that will be located
on the android platform. It will use the features located in the APK alongside machine learning to
predict if an APK is malicious or benign. While certain aspect of the machine learning and
deployment to android generated good outcome, several issues were identified during the
development and testing. |
| first_indexed | 2024-10-01T05:57:20Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/77225 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:57:20Z |
| publishDate | 2019 |
| record_format | dspace |
| spelling | ntu-10356/772252023-03-03T20:58:47Z Malware detection application for android using machine learning Loh, Jing Kai Liu Yang School of Computer Science and Engineering DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Mobile phones especially smartphone is now an essential item in today’s society, granting user’s ability to perform tasks and brining convenience to its user. While IOS popularity is constantly growing, android still commands much of the market share and thus has been seen as a lucrative market for malicious actors to benefit off this huge market. Although a variety of methods exist to protect users from these malicious actors, those solutions tend to have negative drawbacks to them. Thus, new way to be able to detect these malwares is needed. In this project, the focus will be on the development of malware detection tool that will be located on the android platform. It will use the features located in the APK alongside machine learning to predict if an APK is malicious or benign. While certain aspect of the machine learning and deployment to android generated good outcome, several issues were identified during the development and testing. Bachelor of Engineering (Computer Science) 2019-05-17T08:38:50Z 2019-05-17T08:38:50Z 2019 Final Year Project (FYP) http://hdl.handle.net/10356/77225 en Nanyang Technological University 40 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Loh, Jing Kai Malware detection application for android using machine learning |
| title | Malware detection application for android using machine learning |
| title_full | Malware detection application for android using machine learning |
| title_fullStr | Malware detection application for android using machine learning |
| title_full_unstemmed | Malware detection application for android using machine learning |
| title_short | Malware detection application for android using machine learning |
| title_sort | malware detection application for android using machine learning |
| topic | DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence |
| url | http://hdl.handle.net/10356/77225 |
| work_keys_str_mv | AT lohjingkai malwaredetectionapplicationforandroidusingmachinelearning |