Machine Learning for SDN security: improving intrusion and vulnerability detection

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Machine Learning for SDN security: improving intrusion and vulnerability detection

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  • As Software-Defined Networks (SDN) become increasingly widespread, securing them against potential vulnerabilities and intrusions is of utmost importance. In this webinar, we will delve into the current state of the art in SDN security and highlight its significance. Additionally, we will explore the role of Machine Learning (ML) in enhancing intrusion and vulnerability detection within SDN environments. 

     

    Throughout the webinar, we will evaluate recent research on the subject and present a challenge for attendees to engage in. By participating in this challenge, attendees will acquire hands-on experience in developing ML models for detecting vulnerabilities and intrusions in SDNs, while simultaneously deepening their understanding of the critical nature of SDN security. 

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    • Start date
      29 May 2023 at 15:00 CEST Geneva | 09:00-10:00 EDT, New York | 21:00-22:00 CST, Beijing
    • End date
      29 May 2023 at 16:00 CEST Geneva | 09:00-10:00 EDT, New York | 21:00-22:00 CST, Beijing
    • Duration
      60 minutes
    • Programme stream
    • Topics
    • UN SDGs

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