Comparative Simulation of Homomorphic Encryption Techniques in Edge-Cloud Computing: Reducing Computational and Storage Overhead

Homomorphic Encryption (HE) enables secure data processing by allowing computations on encrypted data without decryption which is important for privacy in edge cloud computing. However the high computational and storage overhead of HE makes a significant challenge for edge cloud devices. This study aims to optimize the implementation of HE in an edge cloud computing environment by reducing encryption latency and storage requirements. We propose two optimization techniques: Lazy Bootstrapping and Hybrid Encryption. Using a real world IoT temperature dataset we evaluate and compare three configurations: standard HE, HE with Lazy Bootstrapping, and HE with Hybrid Encryption. Experiment result show that Lazy Bootstrapping reduces encryption time by 25% and ciphertext size by 11.6%, while Hybrid Encryption offers the highest efficiency, reducing encryption time by 76% and ciphertext size by 97,7%. These makes Hybrid Encryption is the most suitable approach for efficient and secure data processing in edge cloud scenarios.