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Adaptive risk management framework for cloud computing

Citation

Medhioub, M and Hamdi, M and Kim, T-H, Adaptive risk management framework for cloud computing, Proceedings - International Conference on Advanced Information Networking and Applications, AINA 2017, 27-29 March 2017, Taipei, Taiwan, pp. 1154-1161. ISSN 1550-445X (2017) [Refereed Conference Paper]

Copyright Statement

Copyright 2017 IEEE.

DOI: doi:10.1109/AINA.2017.143

Abstract

Cloud computing is an emerging economic model that provides a broad network access to services with many benefits to many tenants at the same time. Although it creates a large potential to develop new online services the evolution of cloud computing has been accompanied by the proliferation of various attacks against the services on the cloud infrastructures. The importance of risk management in cloud computing is mainly motivated by the dynamic context in which the services and applications are implemented. In fact, the intrinsic characteristics of cloud infrastructures prevent the use of previously developed process of traditional frameworks. The goal of this paper is top resent a new risk management framework for better considering context parameters of cloud computing environment. An example is considered in which the risk treatment process in this framework proposes how to dynamically balance between the security and performance degradation due to the implementation of security mechanism.

Item Details

Item Type:Refereed Conference Paper
Keywords:cloud computing, risk management, security
Research Division:Information and Computing Sciences
Research Group:Computer Software
Research Field:Computer Software not elsewhere classified
Objective Division:Information and Communication Services
Objective Group:Computer Software and Services
Objective Field:Computer Software and Services not elsewhere classified
Author:Kim, T-H (Dr Tai Kim)
ID Code:118184
Year Published:2017
Deposited By:Information and Communication Technology
Deposited On:2017-07-06
Last Modified:2017-08-28
Downloads:0

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