Secure Multi-Tenant FPGA Platforms: Theory, Methods, and an Integrated Framework for Provenance-Aware, Runtime-Verifiable Cloud Reconfiguration

Abstract

Field-programmable gate arrays (FPGAs) increasingly underpin cloud-scale acceleration services, creating a convergence of reconfigurability, performance, and shared-resource economics. This convergence delivers profound benefits for heterogeneous computing but simultaneously raises unique security, privacy, and trust challenges. This article synthesizes a rigorous theoretical framework and a cohesive methodological approach for secure, multi-tenant FPGA deployment in cloud environments. It draws strictly and exclusively from the provided references to develop a publication-ready, original conceptual and analytical contribution that articulates a layered defensive architecture, runtime verification strategies, access and licensing controls, covert-channel awareness, virtualization and isolation mechanisms, and research pathways for future-proofing FPGA-as-a-service. The work begins by explicating the threat landscape exposed by recent surveys and empirical studies, then integrates formal methods such as proof-carrying hardware for runtime assurances. It elaborates a descriptive methodology for design-time and runtime integration of trust metadata, licensing policy enforcement, tenant isolation, and hardware-monitoring techniques. The results section offers a detailed descriptive analysis of how the proposed framework addresses specific classes of attacks identified in the literature — from IP theft and license circumvention through covert-channel leakage and botnet exploitation — and the interplay of mitigation strategies. A deep discussion follows that interprets the theoretical implications, enumerates limitations of current techniques, and identifies concrete directions for both engineering and empirical research. The article concludes by synthesizing a set of actionable recommendations for research and deployment that align technical mechanisms to policy and economic models for practical, auditable FPGA cloud services. All major claims are supported by the provided literature.