Random Additive Signature Monitoring for Control Flow Error Detection

Due to harsher working environments, soft errors or erroneous bit-flips occur more frequently in microcontrollers during execution. Without mitigation, such errors result in data corruption and control flow errors. Multiple software-implemented mitigation techniques have already been proposed. In this paper, we evaluate seven signature monitoring techniques in seven different test cases. We measure and compare their detection ratios, execution time overhead, and code size overhead. From the gathered results, we derive five requirements to develop an optimal signature monitoring technique. Based on these requirements, we propose a new signature monitoring technique called random additive signature monitoring (RASM). RASM uses signature updates with random values and optimally placed validity checks to detect interblock control flow errors. RASM has a higher detection ratio, lower execution time overhead, and lower code size overhead than the studied techniques.status: publishe