Abstract:
The security models of delegation methods in mobile cloud computing (MCC) play a crucial role in mitigating security threats when offloading device operations to the cloud while ensuring optimal performance. These threats include data breaches, unauthorized access, and loss of control over sensitive data. Although numerous security models have been developed for different delegation methods, categorized under layering, authentication, dynamic offloading, and encryption, none fully satisfy all development security criteria despite extensive research efforts. To address this gap, this paper proposes a decision-modeling approach to identify the most effective security modules for delegation methods in MCC. Such problem falls under multi-criteria decision-making (MCDM) due to (1) the presence of multiple development security criteria, (2) the varying importance of these criteria with inherent ambiguity and uncertainty, and (3) data variation. To achieve this, we developed a fuzzy-weighted zero-inconsistency method (FWZIC) under a probabilistic interval neutrosophic hesitant fuzzy set (PINHFS) and the evaluation based on distance from the average solution (EDAS) technique. In addition, the decision matrix in this paper is constructed by crossing 50 security modules from four delegation methods in MCC, categorized as follows: 23 encryption, 12 authentication, 9 layering, and 6 dynamic offloading modules, evaluated based on 13 development security criteria. The findings of PINHFS-FWZIC method indicate that C7 'Data Security' was the most critical and sensitive evaluation criterion, while C1 'General Security Issue' was the least sensitive. According to the EDAS results, SM_07 ranked highest for layering and encryption-based dele-gation methods. For dynamic offloading, SM_02 and SM_03 achieved the top ranking, while for authentication, SM_02 and SM_03 were also identified as the best security modules. To validate the robustness of the proposed approach, sensitivity analysis, Spearman's correlation coefficient test, and comparative analysis were conducted. The results confirm that the proposed approach provides a comprehensive and reliable method for selecting optimal security modules in MCC delegation methods.
