Mobile cloud computing (MCC) is a domain that stemmed from advances in mobile technology and cloud computing. Although debate continues about the best strategies to preserve privacy and personal data protection in MCC, it is essential to explore the effects of applying privacy by design (PbD) to preserve privacy and personal data protection in MCC. PbD is a general philosophy that demonstrates privacy should not be overviewed as an afterthought, but rather as a first-class requirement in the design of IT systems. This study explores the effects of applying PbD to preserve privacy and personal data protection in MCC, and is focused on the privacy of personal data. In this exploration, a framework using PbD has been demonstrated, and seven hypotheses were formulated. Moreover, a survey was implemented where 386 responses were used to test the formulated hypotheses. The results of this study supported the perceived benefits, cues to action of PbD, and perceived threat are positively and directly related to privacy and personal data protection behavior in MCC. Moreover, the results supported that the perceived barriers are negatively and directly related to privacy and personal data protection behavior in MCC. Overall, the results support the utilization of PbD to preserve privacy and personal data protection in MCC and encourage the practitioners to utilize PbD to preserve privacy and personal data protection in MCC.
As a result of a shift in the world of technology, the combination of ubiquitous mobile networks and cloud computing produced the mobile cloud computing (MCC) domain. As a consequence of a major concern of cloud users, privacy and data protection are getting substantial attention in the field. Currently, a considerable number of papers have been published on MCC with a growing interest in privacy and data protection. Along with this advance in MCC, however, no specific investigation highlights the results of the existing studies in privacy and data protection. In addition, there are no particular exploration highlights trends and open issues in the domain. Accordingly, the objective of this paper is to highlight the results of existing primary studies published in privacy and data protection in MCC to identify current trends and open issues. In this investigation, a systematic mapping study was conducted with a set of six research questions. A total of 1711 studies published from 2009 to 2019 were obtained. Following a filtering process, a collection of 74 primary studies were selected. As a result, the present data privacy threats, attacks, and solutions were identified. Also, the ongoing trends of data privacy exercise were observed. Moreover, the most utilized measures, research type, and contribution type facets were emphasized. Additionally, the current open research issues in privacy and data protection in MCC were highlighted. Furthermore, the results demonstrate the current state-of-the-art of privacy and data protection in MCC, and the conclusion will help to identify research trends and open issues in MCC for researchers and offer useful information in MCC for practitioners.
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