Privacy-by-design framework for privacy and personal data protection in mobile cloud computing / Hussain Mutlaq H Alnajrani

• 主要作者: Hussain Mutlaq H , Alnajrani
• 格式: Thesis
• 出版: 2022
• 主題: QA75 Electronic computers. Computer science; QA76 Computer software

As an outcome of a shift in technology, Mobile Cloud Computing (MCC) has been established using the combination of universal mobile networks and cloud computing. Currently, users move their data to cloud storage due to the limitations of mobile devices. As a result of the significant concern of MCC users, privacy and personal data protection are receiving significant attention in the domain. Privacy and personal data protection are increasingly recognized as key security issues in the domain. Several studies on MCC have been done with attention to privacy and personal data protection. Despite this advancement, no single study developed a Privacy by Design (PbD) framework to preserve Privacy and Personal Data Protection (PPDP) in mobile cloud computing. 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 Information Technology (IT) systems. This thesis aims to develop a PbD framework to preserve PPDP in MCC. In the literature review, a systematic mapping study (SMS) was conducted, and a systematic literature review (SLR) was applied. The SMS identified existing threats and attacks on data privacy, and privacy solutions were proposed on PPDP in MCC. The SLR determined the determinants that influence the preservation of PPDP in MCC. In this research, a framework is projected to preserve PPDP in mobile cloud computing, utilizing PbD. The proposed framework uses PbD visibility and transparency by considering location transparency, laws, and regulations. A survey was conducted to test the formulated hypotheses. In the survey, a questionnaire was circulated and a pilot test with 100 responses was conducted along with the real data collection where 386 responses were received. Both studies utilized the SmartPLS for analysis. The SmartPLS analysis tool was chosen since it is a distinguished software implementation for Partial Least Squares Structural Equation Modeling (PLS-SEM). The results of this research supported the articulated hypothesis (SE = 0.056, β = 0.552, p = 0.000) that cues to action of PbD considering visibility location transparency, laws, and regulations are positively related to privacy and personal data protection behavior in MCC. Furthermore, the outcomes of this research supported the formulated hypothesis (Standard error (SE) =0.001, Sample Beta (β) = 0.003, P-value (p) =0.015) that cues to action of privacy by design considering visibility location transparency, laws, and regulations are positively related to the perceived threat. The result will help to determine the PbD framework to preserve privacy and personal data protection in MCC, showing the relation of the perceived threat with privacy and personal data protection behavior in mobile cloud computing, the relation between cues to action with privacy and personal data protection behavior in MCC, and the relation of cues to action with the perceived threat.