کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4955468 | 1444217 | 2017 | 11 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
PIndroid: A novel Android malware detection system using ensemble learning methods
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
شبکه های کامپیوتری و ارتباطات
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
The extensive use of smartphones has been a major driving force behind a drastic increase of malware attacks. Covert techniques used by the malware make them hard to detect with signature based methods. In this paper, we present PIndroid - a novel Permissions and Intents based framework for identifying Android malware apps. To the best of our knowledge, PIndroid is the first solution that uses a combination of permissions and intents supplemented with Ensemble methods for accurate malware detection. The proposed approach, when applied to 1,745 real world applications, provides 99.8% accuracy (which is best reported to date). Empirical results suggest that the proposed framework is effective in detection of malware apps.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers & Security - Volume 68, July 2017, Pages 36-46
Journal: Computers & Security - Volume 68, July 2017, Pages 36-46
نویسندگان
Fauzia Idrees, Muttukrishnan Rajarajan, Mauro Conti, Thomas M. Chen, Yogachandran Rahulamathavan,