Anonymous and Traceable Group Data Sharing in Cloud Computing Using AES Algorithm. - Hassan Qureshi, Fasee Ur Rehman, Mohammed Ismail, L. Vaishnavi (Mathematical Statistician and Engineering Applications, 2023)
With the increasing demand for data-driven decision making, there is a growing need for secure and privacy-preserving data sharing techniques. In this project, we propose an anonymous and traceable group data sharing system that ensures data confidentiality, data integrity, and data availability. The proposed system employs a hybrid encryption scheme, where the data is encrypted using a symmetric key encryption technique, and the symmetric key is then encrypted using an asymmetric key encryption technique. The system also utilizes a decentralized blockchain network to provide traceability and accountability in the data sharing process. To further enhance privacy, the proposed system employs a group-based access control mechanism, where data access is granted to a group of authorized users instead of individual users. The system also provides anonymity by using pseudonyms to represent the identities of the users in the group. We evaluate the proposed system using real-world datasets and show that it provides high-level security and privacy while allowing efficient data sharing. Our results demonstrate that the proposed system can enable secure and privacy-preserving data sharing in various domains, including healthcare, finance, and education.