  The diverse views of science of security have opened up several alleys
towards applying the methods of science to security. We pursue a different kind
of connection between science and security. This paper explores the idea that
security is not just a suitable subject for science, but that the process of
security is also similar to the process of science. This similarity arises from
the fact that both science and security depend on the methods of inductive
inference. Because of this dependency, a scientific theory can never be
definitely proved, but can only be disproved by new evidence, and improved into
a better theory. Because of the same dependency, every security claim and
method has a lifetime, and always eventually needs to be improved.
  In this general framework of security-as-science, we explore the ways to
apply the methods of scientific induction in the process of trust. The process
of trust building and updating is viewed as hypothesis testing. We propose to
formulate the trust hypotheses by the methods of algorithmic learning, and to
build more robust trust testing and vetting methodologies on the solid
foundations of statistical inference.
