  Cyber resilience is the ability of a system to resist and recover from a
cyber attack, thereby restoring the system's functionality. Effective design
and development of a cyber resilient system requires experimental methods and
tools for quantitative measuring of cyber resilience. This paper describes an
experimental method and test bed for obtaining resilience-relevant data as a
system (in our case -- a truck) traverses its route, in repeatable, systematic
experiments. We model a truck equipped with an autonomous cyber-defense system
and which also includes inherent physical resilience features. When attacked by
malware, this ensemble of cyber-physical features (i.e., "bonware") strives to
resist and recover from the performance degradation caused by the malware's
attack. We propose parsimonious mathematical models to aid in quantifying
systems' resilience to cyber attacks. Using the models, we identify
quantitative characteristics obtainable from experimental data, and show that
these characteristics can serve as useful quantitative measures of cyber
resilience.
