Enjoy the Untrusted Cloud: A Secure, Scalable and Efficient SQL-like Query Framework for Outsourcing Data

TL;DR

This paper introduces QShield, a secure, scalable, and efficient SQL-like query framework leveraging Intel SGX to protect data confidentiality and integrity in untrusted cloud environments, while supporting multi-user access control and ensuring query correctness.

Contribution

The work presents a novel hardware-assisted framework with a lightweight secret sharing scheme and trust proof mechanism to address key revocation and knowledge extractor vulnerabilities.

Findings

QShield guarantees data confidentiality and integrity on untrusted clouds.

The framework supports scalable multi-user access control.

QShield incurs minimal performance overhead.

Abstract

While the security of the cloud remains a concern, a common practice is to encrypt data before outsourcing them for utilization. One key challenging issue is how to efficiently perform queries over the ciphertext. Conventional crypto-based solutions, e.g. partially/fully homomorphic encryption and searchable encryption, suffer from low performance, poor expressiveness and weak compatibility. An alternative method that utilizes hardware-assisted trusted execution environment, i.e., Intel SGX, has emerged recently. On one hand, such work lacks of supporting scalable access control over multiple data users. On the other hand, existing solutions are subjected to the key revocation problem and knowledge extractor vulnerability. In this work, we leverage the newly hardware-assisted methodology and propose a secure, scalable and efficient SQL-like query framework named QShield. Building upon Intel SGX, QShield can guarantee the confidentiality and integrity of sensitive data when being processed on an untrusted cloud platform. Moreover, we present a novel lightweight secret sharing method to enable multi-user access control in QShield, while tackling the key revocation problem. Furthermore, with an additional trust proof mechanism, QShield guarantees the correctness of queries and significantly alleviates the possibility to build a knowledge extractor. We implemented a prototype for QShield and show that QShield incurs minimum performance cost.