Enhancing Cloud Data Security and Storage: Integrating Zero-Knowledge Proofs with Lightweight Homomorphic Encryption for Efficient Deduplication

Das, Sunandan Sekhar (2024) Enhancing Cloud Data Security and Storage: Integrating Zero-Knowledge Proofs with Lightweight Homomorphic Encryption for Efficient Deduplication. Masters thesis, Dublin, National College of Ireland.

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Abstract

The exponential growth of cloud computing has necessitated advanced solutions for secure and efficient data management. This research presents a novel framework that combines Lightweight Fully Homomorphic Encryption (LTFHE), Zero-Knowledge Proofs (ZKP), and deduplication techniques to address the challenges of data security, integrity, and storage efficiency in cloud environments. Based on the SEAL (Simple Encrypted Arithmetic Library) for performing arithmetic operations on encrypted data, the proposed framework facilitates secure computations without compromising privacy. Hence, incorporating the Schnorr-based ZKP protocol guarantees secure data integrity check without compromising the privacy of the user’s data in real-time application. Based on a set of experiments carried out on the Amazon EC2 instances, the framework was benchmarked for efficient performance through file sizes of 1 MB up to 200 MB. The performance analysis substantiates linearity of both encryption and decryption algorithms in relation to the file size however, additional enhancements are required to improve the decryption of bigger file sizes. The ZKP protocol had fairly negligible overhead and at the same time, was highly reliable which proves that it is effective in securing cloud storage. Furthermore, the deduplication procedure also worked effectively in pointing out the duplication of data to ensure reduced storage and overall system efficiency. By using advanced cryptographic techniques this research provides a scalable and practical solution to the cloud security problems. The results presented here lend further support to the practical applicability of the proposed framework for future research and for related technologies in commercial cloud-based storage. Further work will involve fine-tuning the decryption process and expanding on the ways of applying these techniques in large-scale cloud infrastructures.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Samarawickrama, Yasantha UNSPECIFIED
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Cloud computing Q Science > QA Mathematics > Computer software > Computer Security T Technology > T Technology (General) > Information Technology > Computer software > Computer Security
Divisions:	School of Computing > Master of Science in Cloud Computing
Depositing User:	Ciara O'Brien
Date Deposited:	03 Jul 2025 09:19
Last Modified:	03 Jul 2025 09:19
URI:	https://norma.ncirl.ie/id/eprint/8013

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