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Enabling Secure and Efficient Sharing of Accelerators in Expeditionary Systems

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Abstract

The addition of FPGAs in the cloud is an emerging effort to support acceleration and performance with the flexibility of logic reprogramming. The underlying logic per unit area of the FPGA chip has multiplied, making it challenging for a single-user design to utilize completely and efficiently. Major service providers (such as Amazon, Alibaba, and Baidu) are moving toward a shared FPGA model that allows system designers to share the chip fabric either spatially or temporally. This virtual partitioning of FPGAs is comparable to the expeditionary systems that also adhere to the same principle of sharing chip fabric among multiple tenants. These tenants have the potential to execute any untrusted application on this shared hardware, which is a serious cause for concern in expeditionary systems. For instance, a tenant can deploy malicious circuits that compromise the confidentiality, integrity, and availability of its fellow tenants. In this paper, we investigate the threat landscape and propose mitigation strategies for multitenant FPGAs. We assess threats to the confidentiality of users’ critical data that are novel to the FPGA-as-a-Service (FaaS) framework. We present a defense mechanism for cloud FPGAs that verifies the integrity of tenants. In order to safeguard multi-tenant FPGAs from denial-of-service (DoS) attacks, our secondary defense mechanism promptly identifies malicious tenants and notifies the cloud orchestrator, thereby ensuring availability. We offer a comprehensive, all-in-one solution designed to defend and mitigate various threats faced by users in multi-tenant cloud FPGAs (in the public domain). The same principles apply to expeditionary systems with SWAP-constrained devices where multiple (potentially untrusted) applications share the same hardware. The proposed solution is thus adaptable and extendable to both public cloud service providers and expeditionary systems with private cloud infrastructure. The results show that the proposed work offers (i) safe-and-secure isolation of tenants, (ii) run-time access policy updates, and (iii) resilience against DoS attacks.

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Notes

  1. Previous research has focused on either obtaining model hyperparameters or extracting secret cryptographic keys, remotely. In contrast, our work focuses on extracting model parameters remotely from an ML accelerator.

  2. Vendors/CSPs may try to prevent this capability by detecting/restricting certain types of malicious circuits. However, these defenses can be bypassed by adversaries, as shown in Section  4.3.

  3. We used Xilinx FD latch primitive to capture the output of buffer at each stage.

  4. Functional verification of these efforts is beyond the scope of this work. This work does not claim these defenses as our own, but lists them for reader convenience.

  5. AXI burst read/write operations.

  6. AXI-Full interface is also supported, we prefer AXI-Lite for design simplicity.

  7. TDC sensor can also be replicated multiple times for monitoring each tenant’s power individually. This allows for more fine-grained control, but at the cost of more area.

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  1. North Carolina State University, Raleigh, NC, USA

    Arsalan Ali Malik, Emre Karabulut, Amro Awad & Aydin Aysu

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Malik, A.A., Karabulut, E., Awad, A. et al. Enabling Secure and Efficient Sharing of Accelerators in Expeditionary Systems. J Hardw Syst Secur (2024). https://doi.org/10.1007/s41635-024-00148-4

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