Abstract
Cloud computing enables data storage and application deployment over the internet, offering benefits such as mobility, resource pooling, and scalability. However, it also presents major challenges, particularly in managing shared resources, ensuring data security, and controlling distributed applications in the absence of centralized oversight. One key issue is data duplication, which leads to inefficient storage, increased costs, and potential privacy and security risks. To address these challenges, this study proposes a post-quantum mechanism that enhances both cloud security and deduplication efficiency. The proposed SALIGP method leverages Genetic Programming and a Geometric Approach, integrating Bloom Filters for efficient duplication detection. The Cryptographic Deduplication Authentication Scheme (CDAS) is introduced, which utilizes blockchain technology to securely store and retrieve files, while ensuring that encrypted access is limited to authorized users. This dual-layered approach effectively resolves the issue of redundant data in dynamic, distributed cloud environments. Experimental results demonstrate that the proposed method significantly reduces computation and communication times at various network nodes, particularly in key generation and group operations. Encrypting user data prior to outsourcing ensures enhanced privacy protection during the deduplication process. Overall, the proposed system leads to substantial improvements in cloud data security, reliability, and storage efficiency, offering a scalable and secure framework for modern cloud computing environments.