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ERMOCTAVE: A Risk Management Framework for IT Systems Which Adopt Cloud Computing

Author

Listed:
  • Masky Mackita

    (ING Bank, B-1040 Brussels, Belgium)

  • Soo-Young Shin

    (Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi 39177, Korea)

  • Tae-Young Choe

    (Department of Computer Engineering, Kumoh National Institute of Technology, Gumi 39177, Korea)

Abstract

Many companies are adapting cloud computing technology because moving to the cloud has an array of benefits. During decision-making, having processed for adopting cloud computing, the importance of risk management is progressively recognized. However, traditional risk management methods cannot be applied directly to cloud computing when data are transmitted and processed by external providers. When they are directly applied, risk management processes can fail by ignoring the distributed nature of cloud computing and leaving numerous risks unidentified. In order to fix this backdrop, this paper introduces a new risk management method, Enterprise Risk Management for Operationally Critical Threat, Asset, and Vulnerability Evaluation (ERMOCTAVE), which combines Enterprise Risk Management and Operationally Critical Threat, Asset, and Vulnerability Evaluation for mitigating risks that can arise with cloud computing. ERMOCTAVE is composed of two risk management methods by combining each component with another processes for comprehensive perception of risks. In order to explain ERMOCTAVE in detail, a case study scenario is presented where an Internet seller migrates some modules to Microsoft Azure cloud. The functionality comparison with ENISA and Microsoft cloud risk assessment shows that ERMOCTAVE has additional features, such as key objectives and strategies, critical assets, and risk measurement criteria.

Suggested Citation

  • Masky Mackita & Soo-Young Shin & Tae-Young Choe, 2019. "ERMOCTAVE: A Risk Management Framework for IT Systems Which Adopt Cloud Computing," Future Internet, MDPI, vol. 11(9), pages 1-21, September.
    • Handle: RePEc:gam:jftint:v:11:y:2019:i:9:p:195-:d:266017
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    References listed on IDEAS

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    6. Benedikt Martens & Frank Teuteberg, 2012. "Decision-making in cloud computing environments: A cost and risk based approach," Information Systems Frontiers, Springer, vol. 14(4), pages 871-893, September.
    7. Editorial Article, 0. "The Information for Authors," Economics of Contemporary Russia, Regional Public Organization for Assistance to the Development of Institutions of the Department of Economics of the Russian Academy of Sciences, issue 3.
    8. Editorial Article, 0. "The Information for Authors," Economics of Contemporary Russia, Regional Public Organization for Assistance to the Development of Institutions of the Department of Economics of the Russian Academy of Sciences, issue 1.
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    Cited by:

    1. Paniti Netinant & Nattapat Saengsuwan & Meennapa Rukhiran & Sorapak Pukdesree, 2023. "Enhancing Data Management Strategies with a Hybrid Layering Framework in Assessing Data Validation and High Availability Sustainability," Sustainability, MDPI, vol. 15(20), pages 1-28, October.
    2. Qunying Mao, 2023. "Risk management of project information system operation and maintenance based on Cloud Computing," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(1), pages 176-187, February.

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