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This article explores the UK's current approach in addressing the cybersecurity skills gap championed by the National Cyber Security Strategy. There have been progressive and elaborate steps taken in the UK toward professionalization of the cybersecurity field. However, cybersecurity knowledge has been labelled as inconsistent when a cybersecurity Chartered status is being proposed. The objective of this analysis was to apply an academic lens over the UK's voyage towards the establishment of a cybersecurity profession. It has been an ambitious but complex endeavor that at times has had alterations of course. Learning from this experience, a blended learning and development approach is now recommended underpinned by an overarching core knowledge framework. Such a framework could join up the existing silos of learning and development activities to benefit from, and build upon, a coherent core knowledge-base for the community. It is argued that this will provide a more satisfactory outcome to enhance the UK's cybersecurity capability on the road to a cybersecurity profession.

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The severe acute respiratory syndrome coronavirus 2 pandemic revealed that many countries had insufficient strategies to conduct test, track, and trace of the viral transmission once infected people entered a country’s borders. Computer science could be used to understand the seats of infection, and hotspots that may fuel potential outbreaks. As well as the added benefit of steering on-the-ground epidemiological surveillance activities to contain further outbreaks. However, there is more to a computerized solution than an architectural design of an end-to-end distributed test, track, and trace system and its use of machine learning technologies. A successful implementation encompasses a number of key areas that include people, processes, and technology. Comparisons are drawn with cyber security operations center use-cases in support of a strategy and concept of operations to enable: (a) front-end test teams at the border chokepoints to collect test samples; (b) cloud processing of test subject records and laboratory test results; (c) emergency operations center containment monitoring; (d) data analysis of test subject groupings to identify hotspot areas; (e) use of epidemiological trends to direct further testing; and (f) conduct epidemiological monitoring to detect new chains of transmission.

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