A Privacy-Enhanced Framework for Securing User Data on Cloud-Based Social Networks
Nasira Tabassum S, Gangadhara Rao Kancherla · International Journal of Electrical and Electronics Engineering · 2024
Online Social Networks (OSNs) have become integral to modern life, enabling people to communicate, share information, and stay connected over vast distances. However, the rising use of OSNs has sparked significant concerns regarding the privacy and security of user data. This paper presents an innovative method for strengthening data privacy and security in cloud-enabled OSNs utilizing an E-ABE system. The proposed solution employs flow graph analysis to verify relationships, ensuring secure user data exchange while offering fine-grained access control. This approach addresses the limitations of existing methods, which often fail to provide comprehensive privacy and security measures. By leveraging cryptographic techniques and secure communication protocols, the E-ABE model allows for the controlled sharing of sensitive information, ensuring that only authorized users can access data. The system's design includes roles for Cloud Service Providers (CSPs), Trusted Attribute Authorities (TAAs), and end-users (followers and followees), each contributing to the overall security framework. Experimental results demonstrate the effectiveness of the proposed method in reducing key generation time, data encryption and decryption time, and communication costs while maintaining high levels of authorization accuracy. This research contributes to the field by providing a robust solution for protecting user data in cloud-based OSNs, highlighting its potential for broader application in other domains requiring stringent data privacy and security measures.