  This paper surveys the area of Trust Metrics related to security for
autonomous robotic systems. As the robotics industry undergoes a transformation
from programmed, task oriented, systems to Artificial Intelligence-enabled
learning, these autonomous systems become vulnerable to several security risks,
making a security assessment of these systems of critical importance.
Therefore, our focus is on a holistic approach for assessing system trust which
requires incorporating system, hardware, software, cognitive robustness, and
supplier level trust metrics into a unified model of trust. We set out to
determine if there were already trust metrics that defined such a holistic
system approach. While there are extensive writings related to various aspects
of robotic systems such as, risk management, safety, security assurance and so
on, each source only covered subsets of an overall system and did not
consistently incorporate the relevant costs in their metrics. This paper
attempts to put this prior work into perspective, and to show how it might be
extended to develop useful system-level trust metrics for evaluating complex
robotic (and other) systems.
