Lessons learned: Visualizing cyber situation awareness in a network security domain


Part of a book


C. G. Healey, L. Hao, S. E. Hutchinson
Lecture Notes in Computer Science, Theory and Models for Cyber Situation Awareness, vol. 10030, Springer, 2017, pp. 47-65

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APA   Click to copy
Healey, C. G., Hao, L., & Hutchinson, S. E. (2017). Lessons learned: Visualizing cyber situation awareness in a network security domain (Theory and Models for Cyber Situation Awareness, Vol. 10030, pp. 47–65). Springer.


Chicago/Turabian   Click to copy
Healey, C. G., L. Hao, and S. E. Hutchinson. “Lessons Learned: Visualizing Cyber Situation Awareness in a Network Security Domain.” In , 10030:47–65. Theory and Models for Cyber Situation Awareness. Lecture Notes in Computer Science. Springer, 2017.


MLA   Click to copy
Healey, C. G., et al. Lessons Learned: Visualizing Cyber Situation Awareness in a Network Security Domain. Theory and Models for Cyber Situation Awareness, vol. 10030, Springer, 2017, pp. 47–65.


BibTeX   Click to copy

@inbook{c2017a,
  title = {Lessons learned: Visualizing cyber situation awareness in a network security domain},
  year = {2017},
  edition = {Theory and Models for Cyber Situation Awareness},
  journal = {},
  pages = {47-65},
  publisher = {Springer},
  series = {Lecture Notes in Computer Science},
  volume = {10030},
  author = {Healey, C. G. and Hao, L. and Hutchinson, S. E.}
}

Abstract

This chapter discusses lessons learned working with cyber situation awareness and network security domain experts to integrate visualizations into their current workflows. Working closely with network security experts, we discovered a critical set of requirements that a visualization must meet to be considered for use by these domain experts. We next present two separate examples of visualizations that address these requirements: a flexible web-based application that visualizes network traffic and security data through analyst-driven correlated charts and graphs, and a set of ensemble-based extensions to visualize network traffic and security alerts using existing and future ensemble visualization algorithms.


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