Privacy-Preserving Diabetes Analytics using Homomorphic Encryption in the Cloud: A Review

This review investigates the convergence of homomorphic encryption, cloud computing, and the analysis of diabetes data. It brings together recent progress in methods that protect user privacy. The paper also looks at how different system designs work. It then compares how well various homomorphic encryption types perform. These include Partially Homomorphic Encryption (PHE), Somewhat Homomorphic Encryption (SHE), and Fully Homomorphic Encryption (FHE). PHE allows specific operations, like addition or multiplication, on encrypted data. SHE permits a limited number of both addition and multiplication operations. FHE, the most advanced, allows any computation on encrypted data. The study also covers rules about data privacy. This is especially important for laws like HIPAA in the United States and GDPR in Europe. These rules aim to safeguard sensitive health information. Finally, the work offers a visual way to think about processing diabetes data securely in the cloud. This framework helps users understand how their information stays private. It addresses the critical need for secure handling of personal health information in the growing field of cloud-based health analytics.