Homomorphic Encryption for Secure Data Analysis: A Hybrid Approach using PKCS1_OAEP Padding
Shanmukha Aditya G, B. Kruthika, Shinu M. Rajagopal, C. R. Kavitha
Abstract
In today's data-driven world, striking a balance between data utility and privacy is paramount. Homomorphic encryption, a revolutionary cryptographic technique, facilitates computations on encrypted data without decryption. This study addresses the growing demand for secure data analysis, emphasizing the seamless integration of homomorphic encryption in connecting robust data analysis with essential privacy safeguards. Serving as a vital component in this context, this cutting-edge technique proves pivotal in fostering a secure, privacy-centric approach to data analytics. The outcomes underscore its significance, representing a substantial stride towards the evolution of a conscientious and responsible data-driven ecosystem. The achieved results signal progress in harmonizing data utility and privacy, enhancing overall security and ethical data practices without compromising analytical capabilities.