Navigating the Challenges of Statistical Fault Injection in SRAM-FPGA
Trishna Rajkumar, Johnny Öberg · 2024
In the traditional statistical injection, uncertainty regarding failure rates leads to adopting conservative assumptions that maximise sample size. Consequently, fault injection experiments become excessively time-consuming for applications with minimal error margins. To mitigate the limitations of existing approaches, we investigate the potential of Bayesian sampling in minimising the sample size. Preliminary results indicate up to 5 x reduction with an error rate consistently below 1 %.