  Recent developments have made autonomous vehicles (AVs) closer to hitting our
roads. However, their security is still a major concern among drivers as well
as manufacturers. Although some work has been done to identify threats and
possible solutions, a theoretical framework is needed to measure the security
of AVs. In this paper, a simple security model based on defense graphs is
proposed to quantitatively assess the likelihood of threats on components of an
AV in the presence of available countermeasures. A Bayesian network (BN)
analysis is then applied to obtain the associated security risk. In a case
study, the model and the analysis are studied for GPS spoofing attacks to
demonstrate the effectiveness of the proposed approach for a highly vulnerable
component.
