تفاصيل الوثيقة
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نوع الوثيقة |
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مقال في مجلة دورية |
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عنوان الوثيقة |
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Intelligent Approach for Android Malware Detection Intelligent Approach for Android Malware Detection |
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الموضوع |
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علوم حاسبات |
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لغة الوثيقة |
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الانجليزية |
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المستخلص |
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As the Android operating system has become a key target for malware authors, Android protection has become a thriving research area. Beside the proved importance of system permissions for malware analysis, there is a lot of overlapping in permissions between malware apps and goodware apps. The exploitation of them effectively in malware detection is still an open issue. In this paper, to investigate the feasibility of neuro-fuzzy techniques to Android protection based on system permissions, we introduce a self-adaptive neuro-fuzzy inference system to classify the Android apps into malware and goodware. According to the framework introduced, the most significant permissions that characterize optimally malware apps are identified using Information Gain Ratio method and encapsulated into patterns of features. The patterns of features data is used to train and test the system using stratified cross-validation methodologies. The experiments conducted conclude that the proposed classifier can be effective in Android protection. The results also underline that the neuro-fuzzy techniques are feasible to employ in the field. |
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ردمد |
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1976-7277 |
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اسم الدورية |
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TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS |
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المجلد |
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9 |
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العدد |
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8 |
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سنة النشر |
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1436 هـ
2015 م |
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نوع المقالة |
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مقالة علمية |
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تاريخ الاضافة على الموقع |
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Monday, March 7, 2016 |
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الباحثون
| Altyeb Altaher | Altaher, Altyeb | باحث رئيسي | دكتوراه | altypaltaher@gmail.com |
| Shubair M Abdalla | Abdalla, Shubair M | باحث مشارك | | shubair@squ.edu.om |
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الرجوع إلى صفحة الأبحاث
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