An Extensive Study on Biometric based Secure Data Computing Framework for Mobile Cloud Environments

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A. Amali Mary Bastina, Dr. N. Rama

Abstract

               Mobile cloud computing is gaining popularity among mobile users as it is considered as long envisaged vision of computing as a utility. Despite of its popularity, innovative advances in hardware, networking, middleware, and virtual machine technologies have led to an exploration of new, globally distributed mobile cloud computing platforms. Mobile Cloud Computing provides computation and storage from anywhere around the world via the Internet without adopting for purchase of new infrastructure, training, or software licensing. Mobile cloud is a service model which has been used by mobile device for information storage, searching and data mining and multimedia processing. In addition, this advanced computing platform brings many new challenges for data security and access control on the user data stored on cloud servers. As the data users, no longer have physical possession of the outsourced data, makes the data integrity, privacy and authenticity protection in Cloud Computing a very challenging and potentially difficult task. In order to tackle those challenges, cryptography based secure architecture has been employed to effectively disseminate the user to access the data stored by the data owner.  However those techniques further leads to heavy computational time and cost. In this paper, an extensive study has been carried out using biometric based authentication architecture to strengthen the security of data stored in the cloud environment. It is vital and essential task for providing detailed insight on those authentication systems. The efficacy of each model has been demonstrated on single modal and multimodal fusion. Moreover importance of fusion based representatives has been exploited for secure data access paradigm. Finally outline of the proposed methodology as framework to secure data access using biometric based system has been provided. Evaluation of models has been carried out on the processing of the biometric images of the data users.

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