Authors: Dr. Shrikant V. Sonekar, Professor Rohan B Kokate, Miss. Samiksha S Raut
Abstract: Cloud computing has revolutionized the way data is stored, processed, and shared by providing scalable, flexible, and on-demand access to computational resources over the internet. It has enabled individuals, enterprises, and government organizations to efficiently manage large volumes of data without investing heavily in physical infrastructure. Despite these advantages, the rapid adoption of cloud platforms has introduced significant challenges related to data security, privacy preservation, and fine-grained access control. Since data is stored on third-party servers, users lose direct control over their sensitive information, increasing the risk of unauthorized access, insider threats, and data breaches. Traditional encryption techniques such as symmetric and asymmetric cryptography ensure data confidentiality but fail to provide flexible and scalable access control mechanisms in dynamic, multi-user cloud environments. These methods rely heavily on complex key management systems and are not suitable for scenarios where access permissions need to be defined based on user roles, attributes, or contextual conditions. To address these limitations, Attribute-Based Encryption (ABE) has emerged as a powerful cryptographic approach that enables secure and flexible data sharing by enforcing access policies based on user attributes rather than identities. In particular, Ciphertext-Policy Attribute-Based Encryption (CP-ABE) allows data owners to define access structures directly within the encrypted data, ensuring that only users whose attributes satisfy the defined policies can decrypt and access the information. This paper presents the design and implementation of a secure and privacy-preserving data-sharing framework based on CP-ABE in cloud computing environments. The proposed system incorporates advanced security features such as fine-grained access control, secure key generation and distribution, user authentication, and protection against common attacks including collusion attacks and unauthorized data access. Additionally, privacy-preserving mechanisms are integrated to ensure that sensitive user attributes and data remain protected even from cloud service providers. The system architecture includes key components such as data owners, attribute authorities, cloud servers, and data users, working together to provide a secure and efficient data-sharing environment. Experimental evaluation demonstrates that the proposed framework significantly improves data security, reduces the risk of data breaches, and enhances access control efficiency compared to traditional encryption-based systems.
