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With the growing demand for enhanced performance and scalability in cloud applications and systems, data center architectures are evolving to incorporate heterogeneous computing fabrics that leverage CPUs, GPUs, and FPGAs. Unlike traditional processing platforms like CPUs and GPUs, FPGAs offer the unique ability for hardware reconfiguration at run-time, enabling improved and tailored performance, flexibility, and acceleration. FPGAs excel at executing large-scale search optimization, acceleration, and signal processing tasks while consuming low power and minimizing latency. Major public cloud providers, such as Amazon, Huawei, Microsoft, Alibaba, and others, have already begun integrating FPGA-based cloud acceleration services into their offerings. Although FPGAs in cloud applications facilitate customized hardware acceleration, they also introduce new security challenges that demand attention. Granting cloud users the capability to reconfigure hardware designs after deployment may create potential vulnerabilities for malicious users, thereby jeopardizing entire cloud platforms. In particular, multi-tenant FPGA services, where a single FPGA is divided spatially among multiple users, are highly vulnerable to such attacks. This paper examines the security concerns associated with multi-tenant cloud FPGAs, provides a comprehensive overview of the related security, privacy and trust issues, and discusses forthcoming challenges in this evolving field of study.
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A Verified Confidential Computing as a Service Framework for Privacy Preservation
As service providers are moving to the cloud, users are forced to provision sensitive data to the cloud. Confidential computing leverages hardware Trusted Execution Environment (TEE) to protect data in use, no longer requiring users’ trust to the cloud. The emerging service model, Confidential Computing as a Service (CCaaS), is adopted by service providers to offer service similar to the Function-as-a-Serivce manner. However, privacy concerns are raised in CCaaS, especially in multi-user scenarios. CCaaS need to assure the data providers that the service does not leak their privacy to any unauthorized parties and clear their data after the service. To address such privacy concerns with security guarantees, we first formally define the security objective, Proof of Being Forgotten (PoBF), and prove under which security constraints PoBF can be satisfied. Then, these constraints serve as guidelines in the implementation of the PoBF-compliant Framework (PoCF). PoCF consists of a generic library for different hardware TEEs, CCaaS prototype enclaves, and a verifier to prove PoBF-compliance. PoCF leverages Rust’s robust type system and security features, to construct a verified state machine with privacy-preserving contracts. Last, the experiment results show that the protections introduced by PoCF incur minor runtime performance overhead.
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- PAR ID:
- 10506290
- Editor(s):
- Joe Calandrino and Carmela Troncoso
- Publisher / Repository:
- USENIX Association2560 Ninth St. Suite 215 Berkeley, CA, United States
- Date Published:
- Journal Name:
- the Proceedings of the 32nd USENIX Security Symposium
- ISBN:
- 978-1-939133-37-3
- Format(s):
- Medium: X
- Location:
- Anaheim, CA, USA
- Sponsoring Org:
- National Science Foundation
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Accepted Manuscript1.0
- Conference Paper:
- The DOI is not currently available.
