Abstract: The growing reliance on cloud infrastructure for storing and managing relational databases has introduced critical challenges in preserving data confidentiality while enabling efficient query execution. Traditional encryption schemes offer strong data protection but often impede the ability to perform complex SQL operations without decryption, creating a trade-off between security and functionality. Recent advances in privacy-preserving query processing techniques—including homomorphic encryption, searchable encryption, oblivious RAM, and secure multiparty computation—have revolutionized the field by enabling secure computation over encrypted data with minimal performance penalties. This review paper systematically analyzes the state-of-the-art mechanisms that support encrypted SQL query processing in cloud-hosted relational databases. It evaluates the theoretical foundations, computational overheads, query expressiveness, and practical deployment scenarios of these privacy-preserving methods. Furthermore, it explores hybrid approaches that combine cryptographic and hardware-based techniques to balance performance with security guarantees. The paper also highlights emerging trends such as federated SQL processing, data provenance tracking, and secure hardware enclaves that are reshaping privacy-preserving architectures. The study aims to provide a comprehensive understanding of the current capabilities, limitations, and future research directions in secure query execution for encrypted relational databases deployed in cloud environments.
Keywords: Encrypted SQL Query Processing, Homomorphic Encryption, Secure Cloud Databases, Privacy-Preserving Computation, Searchable Encryption, Cloud Data Confidentiality.
Title: Recent Advances in Privacy-Preserving Query Processing Techniques for Encrypted Relational Databases in Cloud Infrastructure
Author: Onuh Matthew Ijiga, Nonso Okika, Semirat Abidemi Balogun,. Ogboji James Agbo, Lawrence Anebi Enyejo
International Journal of Computer Science and Information Technology Research
ISSN 2348-1196 (print), ISSN 2348-120X (online)
Vol. 13, Issue 3, July 2025 - September 2025
Page No: 62-80
Research Publish Journals
Website: www.researchpublish.com
Published Date: 08-July-2025
