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AL-DDoS Attack Detection Optimized with Genetic Algorithms

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Part of the Lecture Notes in Computer Science book series (LNAI,volume 10632)

Abstract

Application Layer DDoS (AL-DDoS) is a major danger for Internet information services, because these attacks are easily performed and implemented by attackers and are difficult to detect and stop using traditional firewalls. Managing to saturate physically and computationally the information services offered on the network. Directly harming legitimate users, to deal with this type of attacks in the network layer previous approaches propose to use a configurable statistical model and observed that when being optimized in various configuration parameters Using Genetic Algorithms was able to optimize the effectiveness to detect Network Layer DDoS (NL-DDoS), however this method is not enough to stop DDoS at the level of application because this level presents different characteristics, that is why we propose a new method Configurable and optimized for different scenarios of Attacks that effectively detect AL-DDoS.

Keywords

  • DDOS
  • Genetic algorithms
  • Variances analysis
  • Security

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  • DOI: 10.1007/978-3-030-02837-4_9
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References

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Correspondence to Julio Santisteban .

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Quequezana-Buendia, J., Santisteban, J. (2018). AL-DDoS Attack Detection Optimized with Genetic Algorithms. In: Castro, F., Miranda-Jiménez, S., González-Mendoza, M. (eds) Advances in Soft Computing. MICAI 2017. Lecture Notes in Computer Science(), vol 10632. Springer, Cham. https://doi.org/10.1007/978-3-030-02837-4_9

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  • DOI: https://doi.org/10.1007/978-3-030-02837-4_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-02836-7

  • Online ISBN: 978-3-030-02837-4

  • eBook Packages: Computer ScienceComputer Science (R0)