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Detecting DDoS Attacks in Cloud Computing Using Extreme Learning Machine and Adaptive Differential Evolution

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Abstract

Distributed denial of service (DDoS) attacks disrupt the availability of cloud services. The detection of these attacks is a major challenge in the cloud computing environment. Machine learning models can be used to detect these attacks efficiently. In this work, a hybrid machine learning model based approach to detect these attacks is proposed. Firstly, a hybrid machine learning model using extreme learning machine (ELM) and adaptive differential evolution is proposed. In the proposed model, input to hidden layer link weights, and hidden layer biases of ELM are optimized using adaptive differential evolution while weights of links between hidden and output layers are analytically determined. The adaptive differential evolution is modified to choose the apt crossover operator during the evolution process. After that, a DDoS attack detection system using the suggested hybrid model is proposed for cloud computing.. Three state-of-the-art datasets NSL-KDD, ISCX IDS 2012, and CIDDS-001 are used to evaluate the performance of the proposed attack detection system.

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Data Availability

NSL-KDD and ISCX IDS 2012 datasets used in this study are available in the UNB CIC repository: https://www.unb.ca/cic/datasets/index.html. CIDDS-001 dataset is available at Coburg-university website: .htmlhttps://www.hs-coburg.de/forschung/forschungsprojekte-oeffentlich/informationstechnologie/cidds-coburg-intrusion-detection-data-sets.

Code Availability

The code of the current study is available from the corresponding author on reasonable request.

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Funding

This research received no grant from any funding agency.

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Author notes

  1. Virender Ranga

    Present address: Information Technology Department, Delhi Technological University, New Delhi, Delhi, India

Authors and Affiliations

  1. Department of Computer Engineering, NIT Kurukshetra, Kurukshetra, Haryana, India

    Gopal Singh Kushwah & Virender Ranga

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  1. Gopal Singh Kushwah
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  2. Virender Ranga
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Contributions

Gopal Singh Kushwah: conceptualization, methodology, software, validation, investigation, writing- original draft. Virender Ranga: resources, supervision, project administration, writing- review and editing.

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Correspondence to Gopal Singh Kushwah.

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Kushwah, G.S., Ranga, V. Detecting DDoS Attacks in Cloud Computing Using Extreme Learning Machine and Adaptive Differential Evolution. Wireless Pers Commun 124, 2613–2636 (2022). https://doi.org/10.1007/s11277-022-09481-9

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