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DDoS Attack Preventing and Detection with the Artificial Intelligence Approach

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Intelligent Computing Systems (ISICS 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1569))

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Abstract

DDoS attacks are a major Internet security concern with this large number of customers. Each attack sends a service request to a certain server, which limits the server’s capacity to provide normal services. Since the attackers use legitimate packages and alter their package information, traditional methods are not very effective. The assault on DDoS is one of the most potent Internet hacking techniques. The hacker’s basic weapon to take down and crash websites during these sorts of assaults is network trafficking. There are different sub-categories, each category explains how a hacker attempts to enter the network. In this paper, we define the DDoS attacks detection method based on artificial intelligence and explored with more than 96-percent accuracy a technique to detect a DDoS attacks assault danger using artificial intelligence (A.I). In addition to a secure or healthy network, authors have identified 7 separate sub-categories of DDoS attacks.

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Author information

Authors and Affiliations

  1. Daffodil International University, Dhaka, Bangladesh

    Tariqul Islam, Md. Ismail Jabiullah & Dm. Mehedi Hasan Abid

Authors
  1. Tariqul Islam
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  2. Md. Ismail Jabiullah
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  3. Dm. Mehedi Hasan Abid
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Corresponding authors

Correspondence to Tariqul Islam , Md. Ismail Jabiullah or Dm. Mehedi Hasan Abid .

Editor information

Editors and Affiliations

  1. Universidad Autónoma de Yucatán, Merida, Mexico

    Carlos Brito-Loeza

  2. Universidad Autónoma de Yucatán, Merida, Mexico

    Anabel Martin-Gonzalez

  3. Universidad de Chile, Santiago, Chile

    Victor Castañeda-Zeman

  4. Higher Colleges of Technology, Abu Dhabi, United Arab Emirates

    Asad Safi

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Islam, T., Jabiullah, M.I., Abid, D.M.H. (2022). DDoS Attack Preventing and Detection with the Artificial Intelligence Approach. In: Brito-Loeza, C., Martin-Gonzalez, A., Castañeda-Zeman, V., Safi, A. (eds) Intelligent Computing Systems. ISICS 2022. Communications in Computer and Information Science, vol 1569. Springer, Cham. https://doi.org/10.1007/978-3-030-98457-1_3

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  • DOI: https://doi.org/10.1007/978-3-030-98457-1_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-98456-4

  • Online ISBN: 978-3-030-98457-1

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