Tim Ellis | Searcharxiv

arXiv2023

Critical Infrastructure Security Goes to Space: Leveraging Lessons Learned on the Ground

Space systems enable essential communications, navigation, imaging and sensing for a variety of domains, including agriculture, commerce, transportation, and emergency operations by first responders. Protecting the cybersecurity of these critical infrastructure systems is essential. While the space environment brings unique constraints to managing cybersecurity risks, lessons learned about risks and effective defenses in other critical infrastructure domains can help us to design effective defenses for space systems. In particular, discoveries regarding cybersecurity for industrial control systems (ICS) for energy, manufacturing, transportation, and the consumer and industrial Internet of Things (IoT) offer insights into cybersecurity for the space domain. This paper provides an overview of ICS and space system commonalities, lessons learned about cybersecurity for ICS that can be applied to space systems, and recommendations for future research and development to secure increasingly critical space systems.

cs.CR↗

arXiv2022

Phase transitions above the upper critical dimension

These lecture notes provide an overview of the renormalization group (RG) as a successful framework to understand critical phenomena above the upper critical dimension $d_{\rm uc}$. After an introduction to the scaling picture of continuous phase transitions, we discuss the apparent failure of the Gaussian fixed point to capture scaling for Landau mean-field theory, which should hold in the thermodynamic limit above $d_{\rm uc}$. We recount how Fisher's dangerous-irrelevant-variable formalism applied to thermodynamic functions partially repairs the situation but at the expense of hyperscaling and finite-size scaling, both of which were, until recently, believed not to apply above $d_{\rm uc}$. We recall limitations of various attempts to match the RG with analytical and numerical results for Ising systems. We explain how the extension of dangerous irrelevancy to the correlation sector is key to marrying the above concepts into a comprehensive RG scaling picture that renders hyperscaling and finite-size scaling valid in all dimensions. We collect what we believe is the current status of the theory, including some new insights and results. This paper is in grateful memory of Michael Fisher who introduced many of the concepts discussed and who, half a century later, contributed to their advancement.

cond-mat.stat-mech↗