An Efficient and Secure Query Processing Framework for Encrypted Databases Leveraging Data Compression Techniques

Abstract:

Distributed computing involves storing data using external storage and accessing it from anywhere, anytime. With the evolution of distributed computing and databases, crucial data finds its place within databases. Yet, as this data resides in outsourced services like Database as

a Service (DaaS), security concerns emerge from both server and client perspectives. Furthermore, the query processing on databases by multiple clients in a shared resource environment can lead to inefficiencies in data processing and retrieval, owing to time- consuming methods. Achieving secure and efficient data retrieval is possible through an effective data processing algorithm employed by various clients. This approach suggests employing a streamlined method via Regressive Probabilistic Key Encryption (RPKE) to enhance query processing efficiency. It involves implementing data compression techniques before transmitting encrypted results from the server to clients. Our strategy for addressing security concerns involves encrypting data at the server-side using CryptDB. Recent advancements in encryption techniques aim to ensure client confidentiality in cloud storage settings. This approach enables query processing using encrypted data without requiring decryption. Evaluating the performance of RPKE involves comparing it with the existing query processing algorithm in CryptDB. The findings indicate a significant improvement in storage efficiency, with space savings of up to 61%.