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International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems

IEA/AIE 2018: Recent Trends and Future Technology in Applied Intelligence pp 454–461Cite as

ACO-Based Measure for SYN Flooding Over Mobile Data Connectivity

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10868))

Abstract

Dynamics in IP-based SYN-flooding, whereby attacker can create slave daemon generators and distribute attacks, have frightened integration of mobile services over mobile data connectivity. This study proposes unsupervised learning model inspired by three ingredients of ants foraging behaviour to improve accuracy in detection of SYN dynamics and reduces the number of falsified alarms. The evaluation establishes simulation environment and analyse collected data using Mean Value Analysis (MVA) method, whereby results prove the model to dynamically classify, detect and wedge-out SYN-flooding at 58.4% utilization of GGSN gateway.

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Author information

Authors and Affiliations

  1. College of Information and Communication Technologies, University of Dar es Salaam, Dar es Salaam, Tanzania

    Joseph C. Mushi, Mussa Kissaka & Kosmas Kapis

Authors
  1. Joseph C. Mushi
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  2. Mussa Kissaka
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  3. Kosmas Kapis
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Corresponding author

Correspondence to Joseph C. Mushi .

Editor information

Editors and Affiliations

  1. University of Regina, Regina, SK, Canada

    Malek Mouhoub

  2. University of Regina, Regina, SK, Canada

    Samira Sadaoui

  3. Concordia University, Montreal, QC, Canada

    Otmane Ait Mohamed

  4. Texas State University, San Marcos, TX, USA

    Moonis Ali

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Cite this paper

Mushi, J.C., Kissaka, M., Kapis, K. (2018). ACO-Based Measure for SYN Flooding Over Mobile Data Connectivity. In: Mouhoub, M., Sadaoui, S., Ait Mohamed, O., Ali, M. (eds) Recent Trends and Future Technology in Applied Intelligence. IEA/AIE 2018. Lecture Notes in Computer Science(), vol 10868. Springer, Cham. https://doi.org/10.1007/978-3-319-92058-0_44

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  • DOI: https://doi.org/10.1007/978-3-319-92058-0_44

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-92057-3

  • Online ISBN: 978-3-319-92058-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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