Cybersecurity Policies and Their Impact on Dynamic Data Driven Application Systems

Tucker, Conrad S.; Burrows, Mathew; Lesniak, Kevin; Klein, Samuel

doi:10.1109/fas-w.2017.175

Cited by 3 publications

(3 citation statements)

References 2 publications

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“…Broniatowski used precisely this approach when exploring the consequences of different system design strategies for flexibility in a simulated intermodal freight transportation network. In addition Tucker et al . used this approach to explore the impact of cybersecurity policies, such as those restricting freedom of speech to protect privacy, on societal adoption of technology.…”

Section: Relationship To Other Standards Of Rigormentioning

confidence: 99%

“…Such approaches have clear analogies to the concepts discussed in this paper. 103 used this approach to explore the impact of cybersecurity policies, such as those restricting freedom of speech to protect privacy, on societal adoption of technology. Such approaches can give researchers confidence that the model generates the predicted simulated results; however, unless they are validated against empirical data, such models have more in common with the axiomatic approaches discussed above-they provide an explanation that can inform hypotheses to be tested and constructs to be validated.…”

Section: Relationship To Mathematical Models Of Complex Systemsmentioning

confidence: 99%

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Assessing causal claims about complex engineered systems with quantitative data: internal, external, and construct validity

Broniatowski

Tucker

2017

Systems Engineering

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Engineers seek to design systems that will produce an intended change in the state of the world. How are we to know if a system will behave as intended? This article addresses ways that this question can be answered. Specifically, we focus on three types of research validity: (1) internal validity, or whether an observed association between two variables can be attributed to a causal link between them; (2) external validity, or whether a causal link generalizes across contexts; and (3) construct validity, or whether a specific set of metrics corresponds to what they are intended to measure. In each case, we discuss techniques that may be used to establish the corresponding type of validity: namely, quasi‐experimental design, replication, and establishment of convergent‐discriminant validity and reliability. These techniques typically require access to data, which has historically been limited for research on complex engineered systems. This is likely to change in the era of “big data.” Thus, we discuss the continued utility of these validity concepts in the face of advances in machine learning and big data as they pertain to complex engineered sociotechnical systems. Next, we discuss relationships between these validity concepts and other prominent approaches to evaluating research in the field. Finally, we propose a set of criteria by which one may evaluate research utilizing quantitative observation to test causal theory in the field of complex engineered systems.

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Section: Relationship To Other Standards Of Rigormentioning

confidence: 99%

Section: Relationship To Mathematical Models Of Complex Systemsmentioning

confidence: 99%

Assessing causal claims about complex engineered systems with quantitative data: internal, external, and construct validity

Broniatowski

Tucker

2017

Systems Engineering

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“…For example, health care is now considered a central field of study to systems engineering, bringing with it attendant concerns about security and privacy of health records. Similarly, although social media are considered by some as “purely social” systems, the expansion of the “Internet of Things” guarantees that they will also provide valuable signals about the performance of socio‐technical systems, meaning that attendant concerns about online security and privacy are also within scope of systems engineering design.…”

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confidence: 99%

Building the tower without climbing it: Progress in engineering systems

Broniatowski

2018

Systems Engineering

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The Engineering Systems (ES) movement set a research agenda that transformed the field of systems engineering. By focusing on complex sociotechnical systems, the ES movement dramatically expanded the scope of the problems that could be addressed by systems engineers, drawing young scholars into the field. ES succeeded in focusing the scholarly community around the concepts of the "ilities"-nontraditional system lifecycle properties-sociotechnical complexity, and system architecture. In this article, I review some of the progress made by scholars in the field, outline directions for future work, and identify challenges facing future progress in systems engineering. Specific attention is given to approaches that emphasize the roles of abstraction hierarchies, contextual interpretation, knowledge sharing, and expertise. I also briefly address the perceived trade-off between academic rigor and practical utility-a perennial concern in the field. In each case, a review of the literature is performed documenting the progress made by the ES community and other scholarly communities whose findings may be synergistic with ours. Finally, I conclude with a proposal for preserving the momentum started by the ES movement by suggesting a forum for diverse scholarly discourse in systems engineering. K E Y W O R D Sarchitecture, language, model-based systems engineering, rigor, Tower of Babel Genesis 11:1-9, trans. Hebrew, JPS, 1985. 1

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