Secure and Policy-Compliant Query Processing on Heterogeneous Computational Storage Architectures


연구 분야: Cryptography



학회: SIGMOD '22: Proceedings of the 2022 International Conference on Management of Data


초록

Computation Storage Architectures (CSA) are increasingly adopted in the cloud for near data processing, where the underlying storage devices/servers are now equipped with heterogeneous cores which enable computation offloading near to the data. While CSA is a promising high-performance architecture for the cloud, in general data analytics also presents significant data security and policy compliance (e.g., GDPR) challenges in untrusted cloud environments. In this paper, we present IronSafe, a secure and policy-compliant query processing system for heterogeneous computational storage architectures, while preserving the performance advantages of CSA in untrusted cloud environments. To achieve these design properties in a computing environment with heterogeneous host (x86) and storage system (ARM), we design and implement the entire hardware and software system stack from the ground-up leveraging hardware-assisted Trusted Execution Environments (TEEs): namely, Intel SGX and ARM TrustZone. More specifically, IronSafe builds on three core contributions: (1) a heterogeneous confidential computing framework for shielded execution with x86 and ARM TEEs and associated secure storage system for the untrusted storage medium; (2) a policy compliance monitor to provide a unified service for attestation and policy compliance; and (3) a declarative policy language and associated interpreter for concisely specifying and efficiently evaluating a rich set of polices. Our evaluation using the TPC-H SQL benchmark queries and GDPR anti-pattern use-cases shows that IronSafe is faster, on average by 2.3x than a host-only secure system, while providing strong security and policy-compliance properties.


Author Profile
Pramod Bhatotia

Technical University of Munich Munich Germany

Germany
Author Profile
Harshavardhan Unnibhavi

Technical University of Munich Munich Germany

Germany
Author Profile
David Cerdeira

Centro ALGORITMI Universidade do Minho Minho Portugal

Dominican Republic

📄 논문 정보

발행 연도 2022년
인용수 4
출판 국가 Dominican Republic, Germany, United Kingdom
사이트 ACM
좋아요 수 0

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