Guided Fault Injection Strategy for Rapid Critical Bit Detection in Radiation-Prone SRAM-FPGA

Fault injection test is vital for assessing the reliability of SRAM-FPGAs used in radiative environments. Considering the scale and complexity of modern FPGAs, exhaustive fault injection is tedious and computationally expensive. A common approach to optimising the injection campaign involves targeting a subset of the configuration memory containing essential and critical bits crucial for the system's functionality. Identifying Essential bits in an FPGA design is often feasible through manufacturer documen-tation. However, detecting Critical bits requires complex reverse engineering to map the correspondence between the configuration bits and the FPGA modules. This task requires substantial amount of details about the logic layout and the bitstream, which is not easily available due to their proprietary nature. In some cases, manual floorplanning becomes necessary, which could impact the performance of the application. Given these limitations, we examine the potential of Monte Carlo Tree Search in guiding the fault injection process to identify critical bits with minimal injections. The key benefit of this approach is its ability to harness the spatial relations among the configuration bits without relying on reverse engineering or offline campaign planning. Evaluation results demonstrate that the proposed approach achieves a 99 % coverage using 18 % fewer injections than traditional methods. Notably, 95% of the critical bits were detected in under 50% injections, achieving at least 2X higher sensitivity to critical bits with a minimal overhead of 0.04%.