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Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

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Ranking data privacy techniques in cloud computing based on Tamir's complex fuzzy Schweizer-Sklar aggregation

Jabbar Ahmmad¹, Hamiden Abd El-Wahed Khalifa², Hafiz Muhammad Waqas¹

¹Department of Mathematics and Statistics, International Islamic University, Islamabad, Pakistan.

Scientific Reports

|July 10, 2025

Summary

Securing cloud data privacy is vital. A new complex fuzzy Schweizer-Sklar approach effectively ranks data privacy techniques, addressing uncertainties in cloud environments.

Keywords:

Cloud computing Decision making Optimization Schweizer-Sklar aggregation operators Tamir’s complex fuzzy set

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Area of Science:

Computer Science
Information Security
Artificial Intelligence

Background:

Cloud computing necessitates robust data privacy solutions for sensitive information.
Effective data privacy techniques are crucial for cloud security and stakeholder trust.
Selecting optimal privacy techniques in complex cloud environments presents significant decision-making challenges.

Purpose of the Study:

To introduce a novel complex fuzzy Schweizer-Sklar aggregation approach for ranking data privacy techniques.
To develop and analyze new aggregation operators within a complex fuzzy framework.
To provide a practical method for prioritizing data privacy strategies in cloud computing.

Main Methods:

Introduction of fundamental Schweizer-Sklar operational laws for a complex fuzzy framework.
Development of complex fuzzy Schweizer-Sklar power average and geometric aggregation operators.
Exploration of properties like Idempotency, Boundedness, and monotonicity, and algorithm development.

Main Results:

A novel method for ranking and prioritizing data privacy techniques in cloud settings was developed.
The approach effectively handles uncertainties and multi-dimensional aspects of privacy evaluation.
An illustrative example and case study demonstrated the practical application and ranking capabilities.

Conclusions:

The proposed complex fuzzy Schweizer-Sklar aggregation approach offers a superior method for data privacy technique selection in cloud computing.
The developed theory provides a robust framework for dealing with complex decision-making in data privacy.
This work enhances cloud security by offering a systematic way to evaluate and prioritize privacy measures.