  Cooperative perception is an essential and widely discussed application of
connected automated vehicles. However, the authenticity of perception data is
not ensured, because the vehicles cannot independently verify the event they
did not see. Many methods, including trust-based (i.e., statistical) approaches
and plausibility-based methods, have been proposed to determine data
authenticity. However, these methods cannot verify data without a priori
knowledge. In this study, a novel approach of constructing a self-proving data
from the number plate of target vehicles was proposed. By regarding the
pseudonym and number plate as a shared secret and letting multiple vehicles
prove they know it independently, the data authenticity problem can be
transformed to a cryptography problem that can be solved without trust or
plausibility evaluations. Our work can be adapted to the existing works
including ETSI/ISO ITS standards while maintaining backward compatibility.
Analyses of common attacks and attacks specific to the proposed method reveal
that most attacks can be prevented, whereas preventing some other attacks, such
as collusion attacks, can be mitigated. Experiments based on realistic data set
show that the rate of successful verification can achieve 70\% to 80\% at rush
hours.
