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In the past decades, a broad range of technological innovations have helped organizations reach new levels of performance and have shaped the economies of the world and societies of the future. However, unexpected events, such as the COVID-19 pandemic and the blocking of the Suez Canal, have shown that many organizations are unprepared to deal with the impact of the disturbances that can occur. Thus, organizations are challenged to include resilience in the design of their Information Systems and Enterprise Architectures (EAs). We respond to this challange and propose a five-step method aimed to help organizations design resilient enterprise architectures to be able to better deal with (un-) expected disturbances. Our method builds upon the 'EA resilience by design' paradigm, combines knowledge from several domains, namely resilience, risk analysis, and EA, and leverages the ArchiMate 3.1 language to model several resilience characteristics. Using a case study at a leading manufacturing organization in the agri-food sector in Lithuania, we demonstrate the applicability of our method and draw some early lessons learned based on our very first evaluation with experts.

In this article, we put forward the substantial challenges in cyber resilience in the domain of autonomous systems and outline foundational solutions to address these challenges. These solutions fall into two broad themes: resilience-by-design and resilience-by-reaction . We use several application drivers from autonomous systems to motivate the challenges in cyber resilience and to demonstrate the benefit of the solutions. We focus on some autonomous systems in the near horizon (autonomous ground and aerial vehicles) and also a little more distant (autonomous rescue and relief). For resilience-by-design , we focus on design methods in software that are needed for our cyber systems to be resilient. In contrast, for resilience-by-reaction , we discuss how to make systems resilient by responding, reconfiguring, or recovering at runtime when failures happen. We also discuss the notion of adaptive execution to improve resilience, execution transparently and adaptively among available execution platforms (mobile/embedded, edge, and cloud). For each of the two themes, we survey the current state, and the desired state and ways to get there. We conclude the paper by looking at the research challenges we will have to solve in the short and the mid-term to make the vision of resilient autonomous systems a reality. This article came out of discussions that started at the NSF-sponsored Grand Challenges in Resilience Workshop held at Purdue in 2019 with the co-authors contributing to going into the depth of the issues and then this article.