Multi-Tenant Cloud FPGA: A Survey on Security, Trust, and Privacy

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 runtime, 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 article 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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Publication Details

Journal
ACM Transactions on Reconfigurable Technology and Systems
Published
2025-01-27
DOI
https://doi.org/10.1145/3713078
Citations
8
Primary Topic
Physical Unclonable Functions (PUFs) and Hardware Security
Type
article
Field-Weighted Citation Impact
15.89
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article

Multi-Tenant Cloud FPGA: A Survey on Security, Trust, and Privacy

Sujan Kumar Saha, Joel Mandebi Mbongue, Erman Nghonda Tchinda, Max Panoff et al.
8 citations
ACM Transactions on Reconfigurable Technology and Systems
Physical Unclonable Functions (PUFs) and Hardware Security
15.89
article

Multi-Tenant Cloud FPGA: A Survey on Security, Trust, and Privacy

Sujan Kumar Saha, Joel Mandebi Mbongue, Erman Nghonda Tchinda, Max Panoff, Muhammed Kawser Ahmed, Christophe Bobda, Peter Mbua
article en
8 citations

Abstract

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 runtime, 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 article 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.

ACM Transactions on Reconfigurable Technology and SystemsVol. 18(2)
University of Florida (US)
Openalex Percentile: Top 1%
Physical Unclonable Functions (PUFs) and Hardware Security
15.89
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Multi-Tenant Cloud FPGA: A Survey on Security, Trust, and Privacy — Sujan Kumar Saha, Joel Mandebi Mbongue, et al. · ACM Transactions on Reconfigurable Technology and Systems (2025) | TGRS Research Map | TGRS