| Autor: |
Sharfah Ratibah Tuan Mat, Mohd Faizal Ab Razak, Mohd Nizam Mohmad Kahar, Juliza Mohamad Arif, Ahmad Firdaus |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
ICT Express, Vol 8, Iss 3, Pp 424-431 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2405-9595 |
| DOI: |
10.1016/j.icte.2021.09.003 |
| Popis: |
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%. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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