Homomorphic Encryption for Granular Privacy in Cloud Computing

Abstract

In the evolving landscape of cloud computing, ensuring data privacy while leveraging cloud infrastructure is a significant challenge. This paper explores the application of homomorphic encryption (HE) as a solution for secure cloud computation, allowing data to remain encrypted while undergoing processing. Homomorphic encryption, which supports operations on ciphertexts, ensures that sensitive information remains protected, even when processed by potentially untrusted cloud service providers. The paper delves into the various types of homomorphic encryption—Partially Homomorphic Encryption (PHE), Somewhat Homomorphic Encryption (SWHE), and Fully Homomorphic Encryption (FHE)—highlighting their capabilities and limitations. While FHE offers the most robust functionality, enabling arbitrary computations on encrypted data, its practical adoption is hindered by significant computational overhead and energy consumption. Case studies demonstrate HE's application in sectors such as finance, healthcare, and government, where data privacy is critical. The paper also addresses the challenges of implementing HE in real-world cloud environments and discusses ongoing research into optimizing HE performance. Finally, it anticipates future trends, including the integration of HE with emerging technologies like quantum computing and blockchain, which promise to broaden its applicability and address current limitations