4.8 Article

Reconsidering big data security and privacy in cloud and mobile cloud systems

Publisher

ELSEVIER
DOI: 10.1016/j.jksuci.2019.05.007

Keywords

Cloud computing; Networked mobile cloud system; Big data security and privacy

Funding

  1. Jordan University of Science and Technology (Jordan)

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Large scale distributed systems, especially cloud and mobile cloud deployments, offer services that improve quality of life and organizational efficiency. Data-driven applications are popular and successful, but also bring challenges like storage, big data processing, and privacy concerns. Solutions using cloud computing, P2P systems, and hybrid mobile cloud models can enhance performance and address these issues.
Large scale distributed systems in particular cloud and mobile cloud deployments provide great services improving people's quality of life and organizational efficiency. In order to match the performance needs, cloud computing engages with the perils of peer-to-peer (P2P) computing and brings up the P2P cloud systems as an extension for federated cloud. Having a decentralized architecture built on independent nodes and resources without any specific central control and monitoring, these cloud deployments are able to handle resource provisioning at a very low cost. Hence, we see a vast amount of mobile applications and services that are ready to scale to billions of mobile devices painlessly. Among these, data driven applications are the most successful ones in terms of popularity or monetization. However, data rich applications expose other problems to consider including storage, big data processing and also the crucial task of protecting private or sensitive information. In this work, first, we go through the existing layered cloud architectures and present a solution addressing the big data storage. Secondly, we explore the use of P2P Cloud System (P2PCS) for big data processing and analytics. Thirdly, we propose an efficient hybrid mobile cloud computing model based on cloudlets concept and we apply this model to health care systems as a case study. Then, the model is simulated using Mobile Cloud Computing Simulator (MCCSIM). According to the experimental power and delay results, the hybrid cloud model performs up to 75% better when compared to the traditional cloud models. Lastly, we enhance our proposals by presenting and analyzing security and privacy countermeasures against possible attacks. (c) 2019 The Authors. Production and hosting by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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