Cloud data privacy protection with homomorphic algorithm: a systematic literature review
Year: 2025
Type: review
Study design: Systematic Review
Abstract: This article critically examines the increasing reliance on cloud computing for data storage and processing, with a focus on the associated security and privacy challenges, especially when handling sensitive data. It explores homomorphic encryption (HE), particularly fully homomorphic encryption (FHE), as a promising solution for enabling computations on encrypted data without compromising confidentiality. Through a systematic literature review of studies published between 2017 and 2024, the article evaluates various homomorphic encryption algorithms, assessing their effectiveness in encryption and decryption, as well as performance metrics such as execution time, communication overhead, and energy consumption. The findings identify FHE as a widely researched technique, yet highlight significant challenges, including high computational overhead and complexity, which limit its suitability for real-time applications. The article underscores the need for continued research to enhance the efficiency of HE algorithms and calls for collaborative efforts among academia, industry, and regulators to establish robust frameworks for data privacy and security in cloud computing environments.
Authors: Michael Ayitey Junior, Peter Appiahene, Obed Appiah, Kwabena Adu
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,790
OpenAlex ID: W7106230640