Ranking data privacy techniques in cloud computing based on Tamir’s complex fuzzy Schweizer-Sklar aggregation approach
Abstract In the era of cloud computing, it has become an important challenge to secure data privacy by storing and processing massive amounts of sensitive information in shared environments. Cloud platforms have become a necessary component for managing personal, commercial, and governmental data. T...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
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| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-09557-z |
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| Summary: | Abstract In the era of cloud computing, it has become an important challenge to secure data privacy by storing and processing massive amounts of sensitive information in shared environments. Cloud platforms have become a necessary component for managing personal, commercial, and governmental data. Thus, the demand for effective data privacy techniques within cloud security frameworks has increased. Data privacy is no longer just an exercise in compliance but rather to reassure stakeholders and protect precious information from cyber-attacks. The decision-making (DM) landscape in the case of cloud providers, therefore, is extremely complex because they would need to select the optimal approach among the very wide gamut of privacy techniques, which range from encryption to anonymization. A novel complex fuzzy Schweizer-Sklar aggregation approach can rank and prioritize data privacy techniques and is particularly suitable for cloud settings. Our method can easily deal with uncertainties and multi-dimensional aspects of privacy evaluation. In this manuscript, first, we introduce the fundamental Schweizer-Sklar operational laws for a cartesian form of complex fuzzy framework. Then relying on these operational laws, we have initiated the notions of cartesian form of complex fuzzy Schweizer-Sklar power average and complex fuzzy Schweizer-Sklar power geometric AOs. We have developed the main properties related to these notions like Idempotency, Boundedness, and monotonicity. Also, we explored an algorithm for the utilization of the developed theory. Moreover, we provided an illustrative example and case study for the developed theory to show the ranking of data privacy techniques in cloud computing. At the end of the manuscript, we discuss the comparative analysis to show the supremacy of the introduced work. |
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| ISSN: | 2045-2322 |