Project Spotlight – Securing Critical Infrastructure

In 2017, LAS is conducting a majority of its research within six different projects, which we call exemplars.  These six exemplars are based around real world challenges that are also aligned to mission needs.  This framework provides realism and relevance to mission users and allows for a common thread that researchers, analysts, academic and industry partners can unite around.  One of these exemplars for 2017 is Securing Critical Infrastructure, which is focusing on applying Anticipatory Thinking within a SmartCity domain.  

The Internet of Things (IoT) has, by many definitions, arrived, with Cisco estimating $4.6 trillion dollars in value at stake for the public sector. Of this, Cisco estimates that cities will generate 63% of the total value at stake. Much of this value will be created from a city’s physical infrastructure (e.g., transportation, power grids and water/gas distribution) being transformed to connected, IoT enabled infrastructure and services.

Historically, value-creating city transformations have had unforeseen, albeit preventable, consequences. The steam revolution transformed commerce but led to industrial slums and air pollution. Electricity provided modern conveniences offset by overly artificial environments.  Finally, the automobile revolution expanded job accessibility at the cost of traffic jams and urban sprawl. City infrastructure transformation has an equivalent, if not greater, potential than the aforementioned transformations. As an example, increasing city revenue and reducing maintenance costs arrives in lock step with anticipated high cyber security costs associated with the IoT. Additionally, there are likely more technological, social and policy factors related to this transformation that we have yet to anticipate.

To anticipate a SmartCity transformation, we turn to a model of deliberately thinking about the future, anticipatory thinking (AT). While similar to prediction in its future-oriented perspective, AT is not based on probabilities and forecasts. Rather, AT is concerned with understanding the conditions under which events occur, their 2nd/3rd/nth order consequences, and the consideration of explicit alternatives to the future. In reference to the previous example, AT would articulate the conditions in which high cyber security costs occur, then derive mitigation plans to ensure the full value-at-stake for SmartCity infrastructure is not eroded. Unfortunately, the tradecraft and definitions supporting AT have not been formalized in a precise enough manner for scientific rigor to augment AT with tools, test AT as skill, or provide training resources.

The project will be developed around three distinct, but connected, areas of investigation.

  1. What factors would enable current and historical technology, social, and policy trends to
    affect the value created by SmartCities?
  2. What properties of AT can be represented by computational models with observed effects in
  3. What modalities are effective for acquiring, retaining, and maintaining AT skills?

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LAS aims to bring together a multi-disciplinary group of academic, industry, and government researchers, analysts and managers together to re-engineer the intelligence analysis process to promote predictive analysis. LAS will do this by conducting both classified and unclassified research in a variety of areas of research. The research done in this area will serve as the foundation for mission effects and integrated back into the enterprise.

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