Multi-Keywords Based Fully Homomorphic Encryption and Data Classification for Cloud Security and Privacy

Multi-Keywords Based Fully Homomorphic Encryption and Data Classification for Cloud Security and Privacy

연구 분야: Cryptography

학회: 2024 2nd International Conference on Emerging Trends in Engineering and Medical Sciences (ICETEMS)

When it comes to processing and storing massive amounts of data efficiently, cloud computing has become the dominant paradigm. Both consumers and suppliers of services in cloud settings are understandably worried about the safety of critical data. When it comes to protecting sensitive information during transmission in the cloud, homomorphic encryption has shown to be an effective method. This study presents a new homomorphic encryption method for efficient and safe computations on the cloud, determined by multistage partial homomorphic encryption. The learning using errors (LWE) issue, primarily an altered form of the BVG method, is the basis of the proposed completely homomorphic encryption technique. It is believed to be difficult to resolve the learning with mistakes issue, which is a challenge in machine learning. We were able to implement the technique by making use of MFHE, an encryption method that can process inputs encrypted under different keys. Our expansion of the technique to search for several keywords was based on this. To make data processing in the cloud safe and privacy protecting, the suggested system combines the strengths of multistage encryption with partial homomorphic encryption.