Shrikhande, Sarang (2024) Enhancing Cloud Security by integrating optimized Symmetric Key Encryption Algorithm in Ethereum Blockchain. Masters thesis, Dublin, National College of Ireland.
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Abstract
Enhancing the Lightweight Bcrypt Symmetric Key (LBSK) encryption algorithm with a data sensitivity classification system provides a balanced solution to modern cloud-based data security challenges. Today, the ever-increasing reliance on cloud service providers (CSPs) for data encryption has led to organizations facing risks such as vendor lock-in and centralized control over their security infrastructure. This method divides data into groups that are sensitive and non-sensitive in order to address these problems. Sensitive data, which demands higher security, is encrypted using the LBSK Encryption algorithm. Meanwhile, non-sensitive data benefits from the Blowfish Encryption Algorithm. This dual approach ensures encryption strength to data sensitivity, optimizing both security and performance. Sensitive data receives enhanced protection through heavier encryption, ensuring robust security, while non-sensitive data is encrypted more efficiently, reducing computational overheads and improving the overall performance. By managing location of encryption keys and file path on a decentralized Ethereum blockchain, this method also decreases dependency on CSPs and provides more control to the user for its data. The findings suggest that this adaptive encryption strategy achieves noteworthy performance improvements for non-sensitive data, with faster encryption times and reduced resource consumption. At the same time, it maintains high security for sensitive data. This solution effectively balances the need for strong data protection with the efficiency demands of modern cloud computing, providing a flexible and practical approach to managing data encryption based on sensitivity.
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