Survey of transformer-based malicious software detection systems

HIGHLIGHTS

• What: In view of this shift in the cybersecurity paradigm this study proposes to discuss the utilization of transformer models to improve malware detection effectiveness and the accuracy and efficiency in detecting malicious software. Most of the existing survey papers are focused on data mining, heuristic-based, signature-based, behavior-based, machine_learning, and deep learning-based techniques for malware detection. The model can focus on several locations of the graph at the same time with the help of a multi-head attention mechanism that derives attention weights that signify the measure of the relatedness of nodes and . . .
  

   

  

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