IDEAS home Printed from https://ideas.repec.org/h/spr/prochp/978-3-031-91524-6_4.html
   My bibliography  Save this book chapter

AI for Network Security

In: Understanding AI in Cybersecurity and Secure AI

Author

Listed:
  • Dilli Prasad Sharma

    (University of Toronto)

  • Arash Habibi Lashkari

    (York University)

  • Mahdi Daghmehchi Firoozjaei

    (MacEwan University)

  • Samaneh Mahdavifar

    (McGill University)

  • Pulei Xiong

    (National Research Council of Canada)

Abstract

The rapid evolution of network architectures has introduced new security challenges, necessitating advanced network protection solutions. This chapter explores the evolution of network security, from traditional firewalls and intrusion detection/prevention systems (IDS/IPS) to modern AI-driven network security solutions. It examines key threat detection approaches, including signature-based, anomaly-based, policy-based, and reputation-based detection, and how AI and machine learning (ML) have transformed network security by enabling automated, adaptive, and real-time threat response mechanisms. The chapter also discusses the future of AI in network security, emphasizing its role in predictive analytics, behavioral analysis, and automated response systems. Additionally, it highlights the challenges and risks associated with AI-based security, such as adversarial attacks, data quality limitations, and integration issues, underscoring the need for continuous advancements in AI-driven defense strategies.

Suggested Citation

  • Dilli Prasad Sharma & Arash Habibi Lashkari & Mahdi Daghmehchi Firoozjaei & Samaneh Mahdavifar & Pulei Xiong, 2025. "AI for Network Security," Progress in IS, in: Understanding AI in Cybersecurity and Secure AI, chapter 0, pages 55-68, Springer.
    • Handle: RePEc:spr:prochp:978-3-031-91524-6_4
    DOI: 10.1007/978-3-031-91524-6_4
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:prochp:978-3-031-91524-6_4. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.