Impact of security risks on cloud computing adoption
ABSTRACT Cloud computing has been a paradigm shift in the information technology domain. It offers potential benefits to users in terms of instant availability, scalability and resource sharing, while potentially posing security issues. Especially, recent events like Amazons system failure increased the concerns related to cloud computing1. Given these security and reliability concerns, we explore the optimal decision rule for moving certain IT function to public clouds. We formulate the problem as an entrepreneurial decision for an optimal stopping time at which the entrepreneur shall migrate to the cloud computing paradigm. Two different models are presented. Recognizing that an important and specific issue related to different computing paradigm is the potential “security” risk posed by each technology, we consider security risks in both models. The first model approaches the optimal adoption problem from assessing the cloud computing adoption under project value uncertainty. The entrepreneur has the timing flexibility and solves his optimal adoption decision under uncertainty. The optimal adoption rule obtained is a threshold strategy. A firm should adopt the cloud computing only if the value from the adoption exceeds the threshold level. The second model builds on a comprehensive assessment of two different computing paradigms. The entrepreneur can either keep the traditional on-site computing paradigm or migrate to the cloud computing paradigm. His problem is to make the paradigm shift optimally. We model such a problem as optimally swapping two “risky” assets, which refer to benefits of the traditional on-site computing paradigm and those of the cloud computing paradigm. The term “risky” captures the fact that actual benefits can only be resolved through time, and thus estimates of benefits are embedded with uncertainty. We obtain the optimal swapping rule as a threshold strategy, defined in terms of the two benefit ratio. A firm should only shift the part of its business to the cloud computing service if the ratio, the benefit from the cloud computing paradigm over that from the traditional on-site computing paradigm, exceeds the threshold. In both models, both the extent of riskiness (i.e. uncertainty) and the significance of security risks (both in terms of potential occurrence probability and the severity of damage) affect the threshold level, thus the entrepreneurial adoption decision.
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ABSTRACT: The cloud computing technology has brought a new era of computing with abundant benefits and ease of operations hiding all the underlying complexities thus providing an efficient platform for all categories of users. Despite of all the assets of cloud computing, its security hinders in its widespread adoption. Among the major deployments of cloud computing i.e. public cloud deployment and private cloud deployment. Private cloud is more secure as it is maintained within the organisation that is using it but at the same time setting up a private cloud infrastructure is an expensive approach. Public cloud is reasonably cost effective due to negligible infrastructure and maintenance cost but it is more vulnerable to security violations. Users need not opt for private clouds if privacy of user data is ensured in public cloud deployment. This paper has focused on the confidentiality issues in public cloud computing environment and to overcome the same, a secure cloud architecture is proposed that enables the user to take full control and ownership of its respective data in public cloud environment. In order to achieve this, hash embedded cryptographic standards have been used, which ensures that the data remains confidential in transit as well as at rest.International Journal of Computer Science Engineering and Information Technology Research (IJCSEITR). 06/2014; 4(3):39-46.
Conference Paper: Confidentiality-preserving optimal power flow for cloud computing[Show abstract] [Hide abstract]
ABSTRACT: In the field of power system engineering, the optimal power flow problem is essential in planning and operations. With increasing system size and complexity, the computational requirements needed to solve practical optimal power flow problems continues to grow. Increasing computational requirements make the possibility of performing these computations remotely with cloud computing appealing. However, power system structure and component values are often confidential; therefore, the problem cannot be shared. To address this issue of confidential information in cloud computing, some techniques for masking optimization problems have been developed. The work of this paper builds upon these techniques for optimization problems but is specifically developed for addressing the DC and AC optimal power flow problems. We study the application of masking a sample OPF using the IEEE 14-bus network.Communication, Control, and Computing (Allerton), 2012 50th Annual Allerton Conference on; 01/2012