In the realm of Autonomous Systems, the absence of direct human oversight introduces novel challenges as these systems start forming complex relationships. The emergent dynamics raise concerns regarding the fair distribution of resources and the promotion of altruistic behavior, which are traditionally moderated by human intervention. This paper envisions an innovative approach that integrates the monetization of acts of generosity in autonomous ecosystems to foster benevolent actions among autonomous agents and, therefore, promote the fairness of the ecosystem as a whole.

With the increasing pervasiveness of software solutions, which are joining cyber-physical spaces and forming partnerships with humans, the importance of the trustworthiness of these systems is growing. At the same time, however, trustworthiness assurance is becoming extremely difficult in these complex ecosystems due to the high autonomy, unpredictability and limited controllability of their individual players. To mitigate safety risks for humans, these Dynamic Autonomous Ecosystems (e.g., Smart Cities) might require their member systems (e.g., Autonomous Vehicles) to execute software modules called Smart Agents to ensure safe coordination among themselves. Unfortunately, this technology is currently in its very early development with many challenges ahead. Namely, there is no guaranteed way of ensuring that these agents run on the right piece of hardware, with the right privileges required to fulfill their roles, and without the execution environment tampering with their instructions. This way, the host system (e.g., the Autonomous Vehicle we need to control for the sake of the safety of other ecosystem members) can escape the actual safety measures to be enforced. In this paper, we are proposing a novel software architecture that focuses on the detection of instruction tampering and privileged access in Smart Agents, and this way support the vision of trustworthy and safe evolution of Dynamic Autonomous Ecosystems.

The evolution of software systems into more complex ecosystems creates new challenges in ensuring their safe and secure behavior. As the complexity of software ecosystems is inherently higher than regular systems, existing safety mechanisms are no longer reliable in their context. This paper introduces a research path towards adaptive safety mechanisms that can support the degree of dynamism and high level of uncertainty introduced by these systems of systems. Our planned approach is to use runtime trust evaluation as a decision factor when enabling or disabling safety features on demand.