Greybox fuzzing has become one of the most effective vulnerability discovery techniques.
However, greybox fuzzing techniques cannot be directly applied to applications in IoT …

Differential testing uses similar programs as cross-referencing oracles to find semantic bugs
that do not exhibit explicit erroneous behaviors like crashes or assertion failures …

Autonomous driving has shown great potential to reform modern transportation. Yet its
reliability and safety have drawn a lot of attention and concerns. Compared with traditional …

Autonomous vehicles use cyber-physical systems to provide comfort and safety to
passengers. Design of safety mechanisms for such systems is hindered by the growing …

Ensuring the safety of autonomous vehicles (AVs) is critical for their mass deployment and
public adoption. However, security attacks that violate safety constraints and cause …

A flurry of fuzzing tools (fuzzers) have been proposed in the literature, aiming at detecting
software vulnerabilities effectively and efficiently. To date, it is however still challenging to …

In high-level Autonomous Driving (AD) systems, behavioral planning is in charge of making
high-level driving decisions such as cruising and stopping, and thus highly securitycritical. In …

Contemporary fuzz testing techniques focus on identifying memory corruption vulnerabilities
that allow adversaries to achieve either remote code execution or information disclosure …

Fuzzing technology has been widely used to discover vulnerabilities, but existing fuzzing
techniques still cannot cover and explore all functions in an application or a library. The …