A multifaceted deep generative adversarial networks model for mobile malware detection

HIGHLIGHTS

• who: Fahad Mazaed Alotaibi and Fawad from the Department of Information Systems, Faculty of Computing and Information Technology (FCIT), King Abdulaziz University, Jeddah, Saudi Arabia have published the paper: A Multifaceted Deep Generative Adversarial Networks Model for Mobile Malware Detection, in the Journal: (JOURNAL)
• what: The models require RGB input images and mostly focus on the input data type; however; 3 of 12 the proposed MDGAN employs the multi-face input consisting of the 2D grayscale image features concatenated to the LSTM binary sequence features set for the detection of malware types. The aim of . . .
  

   

  

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