A survey of low rate ddos detection techniques based on machine learning in software-defined networks

HIGHLIGHTS

  • who: Abdussalam Ahmed Alashhab and collaborators from the Department of Computer and Information Science, Universiti Teknologi Petronas, Seri Iskandar, Faculty of Information Technology, Alasmarya Islamic University, Zliten, Libya have published the paper: A Survey of Low Rate DDoS Detection Techniques Based on Machine Learning in Software-Defined Networks, in the Journal: Symmetry 2022, 14, 1563. of /2022/
  • what: The authors present an extensive survey of different mechanisms proposed to protect the SDN from LDDoS attacks using machine learning approaches. The authors survey various research studies developed for LDDoS detection mechanisms for SDN using machine_learning (ML . . .

     

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