Fortifying Cloud Security with Advanced Data Encryption Technique
DOI:
https://doi.org/10.46243/jst.2025.v10.i03.pp20-27Keywords:
Cloud security,, Homomorphic encryption,, Performance metrics,, Data privacy, Encryption overheadAbstract
The rapid growth of cloud computing has introduced several challenges regarding the securing of sensitive data.
Traditional encryption methods such as those proposed by AES and RSA are unable to efficiently perform with
the scale of large cloud environments as they have high computational cost. Recent advancements that have been
made in encryption methods, especially concerning homomorphic encryption, appear to unravel an unprecedented
potential since they provide capabilities for performing computations on encrypted data without the need to
decrypt it thus assuring the privacy and integrity of data. However, they are still associated with adding
computational overhead, and that will definitely pose various challenges for real-time cloud data processing. The
setup proposed in this paper is a complete framework that integrates homomorphic encryption within a cloud
security environment. It evaluates the effectiveness of homomorphic encryption in the cloud for aspects pertaining
to performance and security, especially in terms of scalability as well with processing huge amounts of sensitive
data while ensuring much efficiency in performance. Further, the framework includes some prior processing like
normalization so as to optimize efficiency in encryption performance. A comprehensive security analysis is
undertaken toward measuring the resistance of such encryption under numerous attack scenarios, and the effect
of quantum computing applications on the proposed method of encryption is also discussed in this regard. This
paper presents a thorough study of performance in conjunction with security trade-offs and, the overall
development of a secure and efficient cloud data processing model.
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