Homomorphic Encryption for Edge Computing Security

Abstract

Homomorphic encryption is a cutting edge security method that can protect sensitive data by performing calculations on encrypted data directly without requiring decryption. This implies that businesses can uphold high data security without sacrificing productivity or adhering to legal requirements. Homomorphic encryption makes it possible to work with encrypted data while maintaining its confidentiality.
This study examines several Homomorphic Encryption (HE) techniques used in edge computing, including BGV, CKKS, RSA, Paillier, and Gentry's. These plans all have different benefits in terms of performance and security. While completely homomorphic encryption was first introduced by Gentry's method, which permits addition and multiplication operations on encrypted data, RSA and Paillier are recognized for their resilience. BGV and CKKS further enhance efficiency and practicality for real world applications.
Significant advantages of homomorphic encryption include decreased latency and enhanced privacy. Nevertheless, the study also discusses excessive energy usage and considerable storage needs. Applications of homomorphic encryption are practical and are emphasized in critical domains such as healthcare, where patient privacy is crucial; smart homes, where secure automation is needed; industrial IoT, where sensitive operational data needs to be protected; autonomous vehicles, where navigational data needs to be protected; and smart cities, where secure data is necessary for effective urban management.