Telecommunications System & Management

Department of Computer Science and Engineering, Qatar University, Doha, Qatar, Qatar University, Qatar

Publications

• Short Communication   
  Transformer and Rapid Selective Kernel Network for DGA Domain Detection
  Author(s): Jose Rashid*
  
  Domain Generation Algorithms (DGAs) are often used by cybercriminals to create large numbers of domain names that can be used for malicious purposes, such as hosting phishing sites, controlling botnets, or spreading malware. These domains are often difficult to detect because they change frequently, making traditional detection methods ineffective. Therefore, the need for more sophisticated detection techniques has arisen, especially in the context of Domain Name System (DNS) traffic analysis. One promising approach to detecting DGA-generated domains is the application of advanced machine learning models, such as the Transformer and Rapid Selective Kernel Network (RSKN). These methods can significantly improve the accuracy and efficiency of DGA domain detection by leveraging their powerful feature extraction and representation capabilities. The Transformer model, originally designed f.. Read More»
  DOI: 10.37421/2167-0919.2024.13.467

  Abstract HTML PDF