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DDoS Attack Detection and Clustering of Attacked and Non-attacked VMs Using SOM in Cloud Network

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Advances in Computing and Data Sciences (ICACDS 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1046))

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Abstract

Cloud computing has gained more importance in the IT service model that offers cost-effective and scalable processing. It provides virtualized and on-demand services to the user over the internet using several networking protocols with exceptional flexibility. However, with the existing technologies and the vulnerabilities, it leads to the occurrence of several attacks in the cloud environment. Distributed Denial of Service (DDoS) is most dangerous among all the attacks which limit the cloud users to access service and resources. Therefore, the detection of DDoS in the network and the identification of attacked VMs is the most dominating task in the cloud environment. In this work, a novel DDoS attack detection mechanism is presented. The research is carried out as follows: (i) Initially DDoS attack is detected by identifying the maximum number of connections to the network, (ii) then the attacked virtual machine and non-attacked virtual machines will be clustered using Self-Organized Mapping (SOM) based Neural Network (NN). The experimental results exhibit that the presented system can efficiently detect DDoS attacks and cluster attack and non-attack VMs in an attacked cloud network. Moreover, these results demonstrate that the proposed DDoS attack prediction accuracy of 97.63% and precision of 95.4% and it is better than the existing technique.

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Authors and Affiliations

  1. Rabindranath Tagore University, Raisen, India

    Nitesh Bharot, Veenadhari Suraparaju & Sanjeev Gupta

Authors
  1. Nitesh Bharot
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  2. Veenadhari Suraparaju
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  3. Sanjeev Gupta
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Corresponding author

Correspondence to Nitesh Bharot .

Editor information

Editors and Affiliations

  1. University of KwaZulu-Natal, Durban, South Africa

    Mayank Singh

  2. Computer Science and Engineering, Jaypee Institute of Information Technology, Waknaghat, Himachal Pradesh, India

    P.K. Gupta

  3. Department of Computer Science and Engineering, Jaypee University of Engineering and Technology, Guna, Madhya Pradesh, India

    Vipin Tyagi

  4. ÚTIA AV ČR, Institute of Information Theory and Automation, Prague 8, Praha, Czech Republic

    Jan Flusser

  5. School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, ON, Canada

    Tuncer Ören

  6. CSE Department, Inderprastha Engineering College, Ghaziabad, Uttar Pradesh, India

    Rekha Kashyap

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Bharot, N., Suraparaju, V., Gupta, S. (2019). DDoS Attack Detection and Clustering of Attacked and Non-attacked VMs Using SOM in Cloud Network. In: Singh, M., Gupta, P., Tyagi, V., Flusser, J., Ören, T., Kashyap, R. (eds) Advances in Computing and Data Sciences. ICACDS 2019. Communications in Computer and Information Science, vol 1046. Springer, Singapore. https://doi.org/10.1007/978-981-13-9942-8_35

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  • DOI: https://doi.org/10.1007/978-981-13-9942-8_35

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-9941-1

  • Online ISBN: 978-981-13-9942-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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