Mitigating Unknown Cybersecurity Threats in Performance Constrained Electronic Control Units

Externally-connected Electronic Control Units (ECUs) contain millions of lines of code, which may contain security vulnerabilities. Hackers may exploit these vulnerabilities to gain code execution privileges, which affect public safety. Traditional Cybersecurity solutions fall short in meeting automotive ECU constraints such as zero false positives, intermittent connectivity, and low performance impact. A desirable solution would be deterministic, require minimum resources, and protect against known and unknown security threats. We integrated Autonomous Security on a BeagleBone Black (BBB) system to evaluate the feasibility of mitigating Cybersecurity risks against potential threats. We identified key metrics that should be measured, such as level of security, ease of integration and system performance impact. In this paper, we describe the integration and evaluation process and present its results. We show that Autonomous Security can provide this protection with zero false-positives while meeting automotive constraints.