4.5 Article Proceedings Paper

Cut and Forward: Safe and Secure Communication for FPGA System on Chips

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCAD.2022.3197343

关键词

Field programmable gate arrays; System-on-chip; Hardware acceleration; Switches; Security; Behavioral sciences; Safety; FPGA system-on-chip (SoC); hardware security; mission-critical systems; on-chip communication

资金

  1. Semiconductor Research Corporation (SRC) [GRC TASK 2993.001]
  2. Intel Scalable Assurance Grant
  3. NSF [1718586]

向作者/读者索取更多资源

Modern FPGA system on chips utilize complex multimanager, multisubordinate on-chip communication networks which may lead to safety and security issues. Cut and forward presents a novel switching method designed to ensure safety and security in multicomponent communication architectures on FPGA systems on chips.
Modern FPGA system on chips uses complex multimanager, multisubordinate on-chip communication networks. Processor cores, hardware accelerators, DMA engines, and other manager components actively access subordinate components like off-chip DRAM, on-chip memories, caches, and I/Os. On-chip communication networks are designed for high bandwidth and low latency. They use simple, fast transactions that largely assumes the managers cooperate. For example, it does not describe default mechanisms to ensure the safe behaviors of the managers using the on-chip interconnect. This lack of specification can lead to unpredictable behaviors: a single misbehaving, misconfigured, or malicious component can cause denial of service of shared resources. Clearly, this issue is critical in systems with safety and security constraints. Cut and forward is a novel switching method for multicomponent communication architectures on FPGA systems on chips (SoCs). Cut and forward leverages the programmability of FPGA SoCs to enable safe and secure bus access and is carefully designed to minimize its impact on performance and resource usage. Experiments show that Cut and forward ensures safety and security in realistic applications deployed on a commercial FPGA SoC from Xilinx including a popular deep neural network accelerator.

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