  Cyberphysical systems (CPS) are ubiquitous in our personal and professional
lives, and they promise to dramatically improve micro-communities (e.g., urban
farms, hospitals), macro-communities (e.g., cities and metropolises), urban
structures (e.g., smart homes and cars), and living structures (e.g., human
bodies, synthetic genomes). The question that we address in this article
pertains to designing these CPS systems to be resilient-from-the-ground-up, and
through progressive learning, resilient-by-reaction. An optimally designed
system is resilient to both unique attacks and recurrent attacks, the latter
with a lower overhead. Overall, the notion of resilience can be thought of in
the light of three main sources of lack of resilience, as follows: exogenous
factors, such as natural variations and attack scenarios; mismatch between
engineered designs and exogenous factors ranging from DDoS (distributed
denial-of-service) attacks or other cybersecurity nightmares, so called "black
swan" events, disabling critical services of the municipal electrical grids and
other connected infrastructures, data breaches, and network failures; and the
fragility of engineered designs themselves encompassing bugs, human-computer
interactions (HCI), and the overall complexity of real-world systems. In the
paper, our focus is on design and deployment innovations that are broadly
applicable across a range of CPS application areas.
