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.
翻译:本文对与自主机器人系统安全有关的信任度量仪领域进行了调查。随着机器人工业从规划、任务导向、系统向人工智能学习转变,这些自主系统很容易受到若干安全风险的影响,因此对这些系统进行至关重要的安全评估。因此,我们的重点是对系统信任进行评估的综合办法,这需要将系统、硬件、软件、认知强力和供应商一级信任度量度纳入一个统一的信任模式。我们着手确定是否存在界定这种整体系统方法的信任度量度。虽然在诸如风险管理、安全、安全保障等方面存在着大量有关机器人系统各个方面的著作,但每个来源只涵盖整个系统的子集,没有始终将相关费用纳入其衡量标准。本文件试图将这一先前的工作纳入到一个统一的信任模式中,并展示如何扩大范围,为评估复杂的机器人系统(和其他)系统制定有用的系统级信任度量度量度。