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Neuro-Fuzzy Model for Assessing Risk in Cloud Computing Environment

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Proceedings of the Second International Afro-European Conference for Industrial Advancement AECIA 2015

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 427))

Abstract

Within a few years, cloud computing emerged as one of the hottest technologies in the IT field. It provides computational resources as general utilities that can be leased and released by users in an on-demand fashion. Cloud computing is rapidly growing interest in many companies around the globe, but adopting cloud computing comes with greater risks, which need to be assessed. In this research, an adaptive neuro-fuzzy inference system (ANFIS) has been applied to assess risk factors in cloud computing. Different membership functions were used for training the data. The model combined the modeling function of fuzzy inference with the learning ability of neural networks. Empirical results illustrate that ANFIS is very effective in modeling cloud-computing risks.

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Acknowledgment

This work was supported by the IT4Innovations Centre of Excellence Project (CZ.1.05/1.1.00/02.0070), funded by the European Regional Development Fund and the national budget of the Czech Republic via the Research and Development for Innovations Operational Programme and by Project SP2015/146 “Parallel Processing of Big Data 2” of the Student Grant System, VŠB-Technical University of Ostrava.

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Authors and Affiliations

  1. Faculty of Computer Science and Information Technology, Sudan University of Science, Technology, Khartoum, Sudan

    Nada Ahmed

  2. College of Computer and Information Sciences, Princess Nourah Bint Abdulrahaman University, Riyadh, South Arabia

    Nada Ahmed

  3. Department of Computer Science and IT4Innovations, Faculty of Electrical Engineering and Computer Science, VŠB-Technical University of Ostrava, Ostrava, Czech Republic

    Ajith Abraham

  4. Machine Intelligence Research Labs (MIR Labs), Scientific Network for Innovation and Research Excellence, Auburn, WA, USA

    Ajith Abraham

Authors
  1. Nada Ahmed
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  2. Ajith Abraham
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Corresponding author

Correspondence to Nada Ahmed .

Editor information

Editors and Affiliations

  1. Sci. Network for Innovation & Rec. Exell, Machine Intelligence Research Labs (MIR, Auburn, Washington, USA

    Ajith Abraham

  2. Membre du Groupe Efrei, ESIGETEL, Villejuif, France

    Katarzyna Wegrzyn-Wolska

  3. Faculty of Computers & Information, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

  4. VSB-Technical University of Ostrava, Ostrava, Czech Republic

    Vaclav Snasel

  5. ENIS, University of Sfax, Sfax, Tunisia

    Adel M. Alimi

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Ahmed, N., Abraham, A. (2016). Neuro-Fuzzy Model for Assessing Risk in Cloud Computing Environment. In: Abraham, A., Wegrzyn-Wolska, K., Hassanien, A., Snasel, V., Alimi, A. (eds) Proceedings of the Second International Afro-European Conference for Industrial Advancement AECIA 2015. Advances in Intelligent Systems and Computing, vol 427. Springer, Cham. https://doi.org/10.1007/978-3-319-29504-6_14

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  • DOI: https://doi.org/10.1007/978-3-319-29504-6_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-29503-9

  • Online ISBN: 978-3-319-29504-6

  • eBook Packages: EngineeringEngineering (R0)

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