The Effectiveness of Homomorphic Encryption in Protecting Data

Privacy.

Abstract

As the use of digital services grows, protecting the privacy and integrity of sensitive data, especially in fields like healthcare, finance, and secure surveying, has become a critical concern. Homomorphic encryption (HE) offers a solution by allowing computations to be performed on encrypted data without revealing the original information. This paper examines the principles of homomorphic encryption and its applications in privacy-preserving tasks, focusing on its use in cloud computing, healthcare, and cybersecurity. Various types of HE schemes, including Fully Homomorphic Encryption (FHE), Partially Homomorphic Encryption (PHE), and Somewhat Homomorphic Encryption (SHE), are reviewed to assess their performance, efficiency, and real-world use. The paper also discusses the challenges of implementing HE, such as computational overhead and key management, and suggests directions for future research to improve the scalability and usability of HE in real-time applications. Addressing these challenges will make homomorphic encryption an essential tool for secure, privacy-preserving data processing and sharing in modern digital systems.

Keywords: Homomorphic encryption, data privacy, cryptography, cloud computing, healthcare security, fully homomorphic encryption, privacypreserving computing, secure data processing, big data, multiparty computation