A Bayesian probability model for Android malware detection
The unprecedented growth of mobile technology has generated an increase in malware and raised concerns over malware threats. Different approaches have been adopted to overcome the malware attacks yet this spread is still increasing. To combat this issue, this study proposes an Android malware detect...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2021
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/32536/ http://umpir.ump.edu.my/id/eprint/32536/1/A%20Bayesian%20probability%20model%20for%20Android%20malware.pdf |
| _version_ | 1848824046170406912 |
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| author | Sharfah Ratibah, Tuan Mat Mohd Faizal, Ab Razak Mohd Nizam, Mohmad Kahar Juliza, Mohamad Arif |
| author_facet | Sharfah Ratibah, Tuan Mat Mohd Faizal, Ab Razak Mohd Nizam, Mohmad Kahar Juliza, Mohamad Arif |
| author_sort | Sharfah Ratibah, Tuan Mat |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | The unprecedented growth of mobile technology has generated an increase in malware and raised concerns over malware threats. Different approaches have been adopted to overcome the malware attacks yet this spread is still increasing. To combat this issue, this study proposes an Android malware detection system based on permission features using Bayesian classification. The permission features were extracted via the static analysis technique. The 10,000 samples for the judgement were obtained from AndroZoo and Drebin databases. The experiment was then conducted using two algorithms for feature selection: information gain and chi-square. The best accuracy rate of detection of permission features achieved was 91.1%. |
| first_indexed | 2025-11-15T03:06:48Z |
| format | Article |
| id | ump-32536 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T03:06:48Z |
| publishDate | 2021 |
| publisher | Elsevier |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-325362021-11-05T04:23:20Z http://umpir.ump.edu.my/id/eprint/32536/ A Bayesian probability model for Android malware detection Sharfah Ratibah, Tuan Mat Mohd Faizal, Ab Razak Mohd Nizam, Mohmad Kahar Juliza, Mohamad Arif QA75 Electronic computers. Computer science The unprecedented growth of mobile technology has generated an increase in malware and raised concerns over malware threats. Different approaches have been adopted to overcome the malware attacks yet this spread is still increasing. To combat this issue, this study proposes an Android malware detection system based on permission features using Bayesian classification. The permission features were extracted via the static analysis technique. The 10,000 samples for the judgement were obtained from AndroZoo and Drebin databases. The experiment was then conducted using two algorithms for feature selection: information gain and chi-square. The best accuracy rate of detection of permission features achieved was 91.1%. Elsevier 2021 Article PeerReviewed pdf en cc_by_4 http://umpir.ump.edu.my/id/eprint/32536/1/A%20Bayesian%20probability%20model%20for%20Android%20malware.pdf Sharfah Ratibah, Tuan Mat and Mohd Faizal, Ab Razak and Mohd Nizam, Mohmad Kahar and Juliza, Mohamad Arif (2021) A Bayesian probability model for Android malware detection. ICT Express. pp. 1-8. ISSN 2405-9595. (In Press / Online First) (In Press / Online First) https://doi.org/10.1016/j.icte.2021.09.003 https://doi.org/10.1016/j.icte.2021.09.003 |
| spellingShingle | QA75 Electronic computers. Computer science Sharfah Ratibah, Tuan Mat Mohd Faizal, Ab Razak Mohd Nizam, Mohmad Kahar Juliza, Mohamad Arif A Bayesian probability model for Android malware detection |
| title | A Bayesian probability model for Android malware detection |
| title_full | A Bayesian probability model for Android malware detection |
| title_fullStr | A Bayesian probability model for Android malware detection |
| title_full_unstemmed | A Bayesian probability model for Android malware detection |
| title_short | A Bayesian probability model for Android malware detection |
| title_sort | bayesian probability model for android malware detection |
| topic | QA75 Electronic computers. Computer science |
| url | http://umpir.ump.edu.my/id/eprint/32536/ http://umpir.ump.edu.my/id/eprint/32536/ http://umpir.ump.edu.my/id/eprint/32536/ http://umpir.ump.edu.my/id/eprint/32536/1/A%20Bayesian%20probability%20model%20for%20Android%20malware.pdf |