Improved Naive Bayes Classifier for Android Malware Classification

@inproceedings{Sayfullina2015ImprovedNB,
  title={Improved Naive Bayes Classifier for Android Malware Classification},
  author={Luiza Sayfullina and Emil Eirola and Dmitry Komashinsky and Paolo Palumbo and Yoan Mich{\'e} and Amaury Lendasse and Juha Karhunen},
  year={2015}
}
According to a recent F-secure report, 97% of mobile malware is designed for the Android platform which has a growing number of consumers. In order to protect consumers from downloading malicious applications, there should be an effective system of malware classification, that can detect previously unseen viruses. In this paper, we present a scalable and highly accurate method for malware classification based on features extracted from Android application package (APK) files. We explored… CONTINUE READING

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