Abstract
The adoption process of innovative software-intensive technologies leverages complex trust concerns in different forms and shapes. Perceived safety plays a fundamental role in technology adoption, being especially crucial in the case of those innovative software-driven technologies characterized by a high degree of dynamism and unpredictability, like collaborating autonomous systems. These systems need to synchronize their maneuvers in order to collaboratively engage in reactions to unpredictable incoming hazardous situations. That is however only possible in the presence of mutual trust. In this paper, we propose an approach for machine-to-machine dynamic trust assessment for collaborating autonomous systems that supports trust-building based on the concept of dynamic safety assurance within the collaborative process among the software-intensive autonomous systems. In our approach, we leverage the concept of digital twins which are abstract models fed with real-time data used in the run-time dynamic exchange of information. The information exchange is performed through the execution of specialized models that embed the necessary safety properties. More particularly, we examine the possible role of the Digital Twins in machine-to-machine trust building and present their design in supporting dynamic trust assessment of autonomous drones. Ultimately, we present a proof of concept of direct and indirect trust assessment by employing the Digital Twin in a use case involving two autonomous collaborating drones.
Abstract (translated)
创新的软件密集型技术的采用过程利用了不同形式和形状的复杂的信任问题。 perceived safety 在技术采用中扮演着至关重要的角色，特别是在那些具有高度活力和不可预测性的软件驱动技术，如协作自主系统。这些系统需要同步他们的行动，以合作应对不可预测的 incoming 危险情况。然而，只有在存在相互信任的情况下才能实现这一点。 在本文中，我们提出了一种方法，用于对协作自主系统进行机器间动态信任评估，该方法支持基于动态安全保证概念在软件密集型自主系统之间的合作过程中建立信任。在这种方法中，我们利用数字双胞胎的概念，它们是带有实时数据用于 Run-time 动态信息交换的抽象模型。信息交换是通过执行包含必要安全属性的特殊模型实现的。更为特别地，我们研究了数字双胞胎在机器间信任建立中的作用，并介绍了它们的设计，以支持自主无人机的动态信任评估。最终，我们使用数字双胞胎在一个涉及两个自主协作无人机的使用案例中证明了直接和间接信任评估的概念。
URL
https://arxiv.org/abs/2303.12805
