Android mobile malware detection using Fuzzy AHP
Android mobile is very challenging because it is an open-source operating system that is also vulnerable to attacks. Previous studies have shown various mobile malware detection methods to overcome this problem, but still, there is room for improvement. Mobile users mostly ignore long lists of permi...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2021
|
| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/31625/ http://umpir.ump.edu.my/id/eprint/31625/7/Android%20Mobile%20Malware%20Detection%20Using%20Fuzzy%20AHP-1.pdf |
| _version_ | 1848823814740246528 |
|---|---|
| author | Juliza, Mohamad Arif Mohd Faizal, Ab Razak Sharfah Ratibah, Tuan Mat Suryanti, Awang Nor Syahidatul Nadiah, Ismail Ahmad Firdaus, Zainal Abidin |
| author_facet | Juliza, Mohamad Arif Mohd Faizal, Ab Razak Sharfah Ratibah, Tuan Mat Suryanti, Awang Nor Syahidatul Nadiah, Ismail Ahmad Firdaus, Zainal Abidin |
| author_sort | Juliza, Mohamad Arif |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | Android mobile is very challenging because it is an open-source operating system that is also vulnerable to attacks. Previous studies have shown various mobile malware detection methods to overcome this problem, but still, there is room for improvement. Mobile users mostly ignore long lists of permissions because these are difficult to understand. Therefore, to distinguish benign or malware applications and the probability of each permission request is understood, it is necessary to evaluate Android mobile applications. This research proposed a multi-criteria decision-making based (MCDM) mobile malware detection system using a risk-based fuzzy analytical hierarchy process (AHP) approach to evaluate the Android mobile application. This study focuses on static analysis, that uses permission-based features to assess the mobile malware detection system approach. Risk analysis is applied to increase the awareness of the mobile user in granting any permission request to contain a high-risk level. The evaluation used 10,000 samples taken from Drebin and AndroZoo. The results show a high accuracy rate of 90.54% values that can effectively classify the Android application into four different risk levels. |
| first_indexed | 2025-11-15T03:03:07Z |
| format | Article |
| id | ump-31625 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T03:03:07Z |
| publishDate | 2021 |
| publisher | Elsevier |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-316252024-01-04T01:42:08Z http://umpir.ump.edu.my/id/eprint/31625/ Android mobile malware detection using Fuzzy AHP Juliza, Mohamad Arif Mohd Faizal, Ab Razak Sharfah Ratibah, Tuan Mat Suryanti, Awang Nor Syahidatul Nadiah, Ismail Ahmad Firdaus, Zainal Abidin QA Mathematics QA75 Electronic computers. Computer science QA76 Computer software Android mobile is very challenging because it is an open-source operating system that is also vulnerable to attacks. Previous studies have shown various mobile malware detection methods to overcome this problem, but still, there is room for improvement. Mobile users mostly ignore long lists of permissions because these are difficult to understand. Therefore, to distinguish benign or malware applications and the probability of each permission request is understood, it is necessary to evaluate Android mobile applications. This research proposed a multi-criteria decision-making based (MCDM) mobile malware detection system using a risk-based fuzzy analytical hierarchy process (AHP) approach to evaluate the Android mobile application. This study focuses on static analysis, that uses permission-based features to assess the mobile malware detection system approach. Risk analysis is applied to increase the awareness of the mobile user in granting any permission request to contain a high-risk level. The evaluation used 10,000 samples taken from Drebin and AndroZoo. The results show a high accuracy rate of 90.54% values that can effectively classify the Android application into four different risk levels. Elsevier 2021 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/31625/7/Android%20Mobile%20Malware%20Detection%20Using%20Fuzzy%20AHP-1.pdf Juliza, Mohamad Arif and Mohd Faizal, Ab Razak and Sharfah Ratibah, Tuan Mat and Suryanti, Awang and Nor Syahidatul Nadiah, Ismail and Ahmad Firdaus, Zainal Abidin (2021) Android mobile malware detection using Fuzzy AHP. Journal of Information Security and Applications, 61 (102929). pp. 1-35. ISSN 2214-2126. (Published) https://doi.org/10.1016/j.jisa.2021.102929 https://doi.org/10.1016/j.jisa.2021.102929 |
| spellingShingle | QA Mathematics QA75 Electronic computers. Computer science QA76 Computer software Juliza, Mohamad Arif Mohd Faizal, Ab Razak Sharfah Ratibah, Tuan Mat Suryanti, Awang Nor Syahidatul Nadiah, Ismail Ahmad Firdaus, Zainal Abidin Android mobile malware detection using Fuzzy AHP |
| title | Android mobile malware detection using Fuzzy AHP |
| title_full | Android mobile malware detection using Fuzzy AHP |
| title_fullStr | Android mobile malware detection using Fuzzy AHP |
| title_full_unstemmed | Android mobile malware detection using Fuzzy AHP |
| title_short | Android mobile malware detection using Fuzzy AHP |
| title_sort | android mobile malware detection using fuzzy ahp |
| topic | QA Mathematics QA75 Electronic computers. Computer science QA76 Computer software |
| url | http://umpir.ump.edu.my/id/eprint/31625/ http://umpir.ump.edu.my/id/eprint/31625/ http://umpir.ump.edu.my/id/eprint/31625/ http://umpir.ump.edu.my/id/eprint/31625/7/Android%20Mobile%20Malware%20Detection%20Using%20Fuzzy%20AHP-1.pdf |