FHG-PR: a hybridized fuzzy-AHP and game theory model for assessing privacy risk on social media platforms

Abstract

Social media platforms have become integral to our daily lives, enabling global connectivity and interaction. Current research provides general solutions for mitigating privacy risks, but it does not focus on particular platforms. However, the voluntary sharing of personal information on these platforms presents considerable privacy risks, highlighting the need for effective risk assessment mechanisms. This study presents a hybrid approach that uses the fuzzy Analytical Hierarchy Process (AHP) and game theory to estimate privacy risks on Meta and X. We used a fuzzy AHP to rank determinant variables based on surveys of social media users and professionals. These weighted criteria were then used in a Multi-Criteria Decision-Making (MCDM) framework using cooperative game theory to discover ways to lower privacy hazards. The model accurately analyzed the privacy threats on Meta and X, recommending alternate techniques for preventing breaches in data privacy. The cooperative game theory method allows stakeholders to collaborate on creating privacy-preserving measures. The findings emphasize the model’s ability to address platform-specific privacy threats, as well as its flexibility in other social media settings. The model’s potential for real-world application is demonstrated by its ability to provide practical risk reduction measures, which improve privacy protection for social media users.