Mobile malware classification based on permission data (İzin verileri kullanılarak mobil kötücül yazılımların sınıflandırılması)
Egemen, Ece and İnal, Ali Emre and Levi, Albert (2015) Mobile malware classification based on permission data (İzin verileri kullanılarak mobil kötücül yazılımların sınıflandırılması). In: 23th Signal Processing and Communications Applications Conference (SIU 2015), Malatya, Turkey
Official URL: http://dx.doi.org/ 10.1109/SIU.2015.7130137
The prevalence of mobile devices in today's world caused the security of these devices questioned more frequently than ever. Android, as one of the most widely used mobile operating systems, is the most likely target for malwares through third party applications. In this work, a method has been devised to detect malwares that target Android platform, by using classification based machine learning. In this study, we use permissions of applications as the features. After the training and test steps on the dataset consisting 5271 malwares and 5097 goodwares, we conclude that Random Forest classification results in 98% performance on the classification of applications. This work emphasizes how much mobile malware classification result can be improved by a system using only the permissions data.
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