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• Empirical Analysis of Forest Penalizing Attribute and Its Enhanced Variations for Android Malware Detection

  Publication

  • A. G. Akintola
  • A. O. Balogun
  • L. F. Capretz
  • H. A. Mojeed
  • S. Basri
  • S. A. Salihu
  • F. E. Usman-Hamza
  • P. O. Sadiku
  • G. B. Balogun
  • Z. O. Alanamu

  - Applied Sciences-Basel - Year 2022

  As a result of the rapid advancement of mobile and internet technology, a plethora of new mobile security risks has recently emerged. Many techniques have been developed to address the risks associated with Android malware. The most extensively used method for identifying Android malware is signature-based detection. The drawback of this method, however, is that it is unable to detect unknown malware. As a consequence of this problem,...

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