Secure Query on Encrypted Data by Using Fully Homomorphic Encryption

Abstract

Cloud service providers typically store user data in an encrypted form (data at rest). However, when a user performs a query, the server first decrypts the data, processes the query on plaintext, and then sends the result back to the user (data in transit). This process exposes a critical vulnerability—if the cloud server is ever compromised, the decrypted data becomes accessible to the attacker. To address this security gap, we design a secure query protocol that eliminates the need to decrypt data on the server side. Fully Homomorphic Encryption (FHE) offers a groundbreaking solution by enabling arbitrary computations directly on encrypted data. This means that even complex queries can be performed without ever revealing the underlying plaintext, and the resulting ciphertext can be decrypted by the user to obtain the correct result. This thesis presents a comprehensive framework for executing secure queries on en- crypted datasets using FHE. We introduce protocols for encrypting and decrypting both individual integers and structured CSV files, ensuring end-to-end data confidential- ity during storage and processing. Additionally, we implement various operations on en- crypted data, including arithmetic operations (addition, multiplication), comparison operations (equal, not equal, greater than, less than, etc.), and data operations such as minimum, maximum, and sorting. Our approach enables secure, database-style querying over encrypted data in un- trusted cloud environments, making it highly relevant for privacy-preserving cloud computing. We provide detailed benchmarks to evaluate the performance and accu- racy of our operations, offering insights into the practicality and limitations of current FHE schemes. The results demonstrate the feasibility of secure cloud-based data analytics through homomorphic encryption.