Enhancing Healthcare Data Security Using Quantum Homomorphic Encryption
Sivaranjani Reddi, Jami Venkata Suman
This chapter presents a novel approach to securing sensitive healthcare data using quantum homomorphic encryption (QHE) integrated with the RSA encryption scheme. In an era where privacy-preserving data analysis is critical, particularly in healthcare, this method demonstrates how encrypted medical datasets, specifically the Diabetes dataset, can undergo computations such as homomorphic addition without compromising confidentiality. The chapter simulates encryption, quantum circuit-based homomorphic operations, and decryption using classical and quantum paradigms. It compares computational accuracy and efficiency between quantum and classical homomorphic models, establishing the feasibility of QHE for real-world medical applications. Performance is evaluated across multiple input sizes, demonstrating secure computation scalability. The results show that QHE offers promising capabilities for privacy-preserving analytics in healthcare and other sensitive domains, bridging quantum and classical cryptographic methods to support secure, efficient, and scalable data processing.
CRC Press eBooks•Nov 28, 2025•0 citations