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Author (up) Campo-Vázquez, C.; García-Rubio, C.; Moure-Garrido, M. url  doi
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  Title Real time detection of malicious DoH traffic using statistical analysis Type Journal Article
  Year 2023 Publication COMPUTER NETWORKSn Abbreviated Journal  
  Volume 234 Issue 109910 Pages 1-10  
  Keywords classification, compromise, computer science, cynamon, dns tunnels, doh traffic, intrusion detection system, malicious doh, Qursa, statistical analysis  
  Abstract The DNS protocol plays a fundamental role in the operation of ubiquitous networks. All devices connected to these networks need DNS to work, both for traditional domain name to IP address translation, and for more advanced services such as resource discovery. DNS over HTTPS (DoH) solves certain security problems present in the DNS protocol. However, malicious DNS tunnels, a covert way of encapsulating malicious traffic in a DNS connection, are difficult to detect because the encrypted data prevents performing an analysis of the content of the DNS traffic. In this study, we introduce a real-time system for detecting malicious DoH tunnels, which is based on analyzing DoH traffic using statistical methods. Our research demonstrates that it is feasible to identify in real-time malicious traffic by analyzing specific parameters extracted from DoH traffic. In addition, we conducted statistical analysis to identify the most significant features that distinguish malicious traffic from benign traffic. Using the selected features, we achieved satisfactory results in classifying DoH traffic as either benign or malicious.  
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  Series Volume Series Issue Edition  
  ISSN 1389-1286 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number UC3M @ josealga @ campo002 Serial 17  
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