An Aggregated Mutual Information Based Feature Selection with Machine Learning Methods for Enhancing IoT Botnet Attack Detection

Mohammed Al-Sarem, Faisal Saeed*, Eman H. Alkhammash, Norah Saleh Alghamdi*

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    24 Citations (SciVal)
    Original languageEnglish
    Article number185
    JournalSensors (Switzerland)
    Volume22
    Issue number1
    DOIs
    Publication statusPublished (VoR) - 28 Dec 2021

    Funding

    This work is supported by Taif University Researchers Supporting Project number (TURSP-2020/292) Taif University, Taif, Saudi Arabia. In addition, this research was funded by the Deanship of Scientific Research at Princess Nourah bint Abdulrahman University through the Fast-track Research Funding Program to support publication in the top journal (Grant no. 42-FTTJ-93).

    FundersFunder number
    Deanship of Scientific Research at Princess Nourah bint Abdulrahman University42-FTTJ-93
    Taif UniversityTURSP-2020/292

      Keywords

      • intrusion detection systems; Internet of Things; botnet attack detection; feature selection; machine learning; ensemble methods

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