A Task Centered Framework for Computer Security Data Visualization

  • Xiaoyuan Suo
  • Ying Zhu
  • Scott Owen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5210)


Most of the existing computer security visualization programs are data centered. However, some studies have shown that task centered visualization is perhaps more effective. To test this hypothesis, we have developed a new framework of visualization and apply it to computer security visualization. This framework provides a new way for users to interact with data set and potentially will provide new insights into how visualization can be better constructed to serve users’ specific tasks.


visualization task computer security 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Mackinlay, J.: Automating the Design of Graphical Presentations of Relational Information. ACM Transactions on Graphics 5, 110–141 (1986)CrossRefGoogle Scholar
  2. 2.
    Cleveland, W.S., McGill, R.: Graphical Perception: Theory, Experimentation, and Application to the Development of Graphical Methods. Journal of the American Statistical Association 79, 531–554 (1984)CrossRefMathSciNetGoogle Scholar
  3. 3.
    Cleveland, W.S., McGill, R.: Graphical Perception and Graphical Methods for Analyzing Scientific Data. Science 229, 828–833 (1985)CrossRefGoogle Scholar
  4. 4.
    Dastani, M.: The Role of Visual Perception in DataVisualization. Journal of Visual Languages and Computing 13, 601–622 (2002)CrossRefGoogle Scholar
  5. 5.
    Wattenberg, M., Fisher, D.: Analyzing perceptual organization in information graphics. Information Visualization 3, 123–133 (2004)CrossRefGoogle Scholar
  6. 6.
    Cox, R.: Representation construction, externalised cognition and individual differences. Learning and Instruction 9, 343–363 (1999)CrossRefGoogle Scholar
  7. 7.
    Freedman, E.G., Shah, P.: Toward a Model of Knowledge-Based Graph Comprehension. In: Hegarty, M., Meyer, B., Narayanan, N.H. (eds.) Diagrams 2002. LNCS (LNAI), vol. 2317, pp. 59–141. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  8. 8.
    Goodall, J.R., Lutters, W.G., Rheingans, P., Komlodi, A.: Preserving the Big Picture: Visual Network Traffic Analysis with TNV. In: Workshop on Visualization for Computer Security, Minneapolis, MN, USA, pp. 47–54 (2005)Google Scholar
  9. 9.
    Abdullah, K., Lee, C., Conti, G., Copeland, J.A., Stasko, J.: IDS RainStorm: Visualizing IDS Alarms. In: IEEE Symposium on Information Visualization’s Workshop on Visualization for Computer Security (VizSEC) (2005)Google Scholar
  10. 10.
    McPherson, J., Ma, K.-L., Krystosk, P., Bartoletti, T., Christensen, M.: PortVis: a tool for port-based detection of security events. In: Proceedings of the 2004 ACM workshop on Visualization and data mining for computer security, ACM Press, Washington (2004)Google Scholar
  11. 11.
    Conti, G.: Security Data Visualization: Graphical Techniques for Network Analysis. No Starch Press (2007)Google Scholar
  12. 12.
    Viegas, F.B., Wattenberg, M., Ham, F.v., Kriss, J., McKeon, M.: Many Eyes: A Site for Visualization at Internet Scale. In: Proceedings of the IEEE Symposium on Information Visualization (2007)Google Scholar
  13. 13.
    Marks, J., Andalman, B., Beardsley, P.A., Freeman, W., Gibson, S., Hodgins, J., Kang, T.: Design Galleries: A General Approach to Setting Parameters for Computer Graphics and Animation. In: Proceedings of ACM SIGGRAPH Conference (1997)Google Scholar
  14. 14.
    Terry, M.: Set-Based User Interface, in PhD Thesis, School of Computing, Georgia Institute of Technology, Atlanta, Georgia (2005)Google Scholar
  15. 15.
    Bratko, I.: PROLOG Programming for Artificial Intelligence, 2nd edn. Addison-Wesley Longman Publishing Co., Inc., Amsterdam (1990)Google Scholar
  16. 16.
    Pain, H., Bundy, A.: What stories should we tell novice PROLOG programmers? In: Artificial intelligence programming environments, pp. 119–130. John Wiley & Sons, New York (1987)Google Scholar
  17. 17.
    Simmons, R., Apfelbaum, D.: A Task Description Language for Robot Control. In: Proceedings of the 1998 IEEE/RSJ International Conference on Intelligent Robots and Systems, Victoria, B.C., Canada (1998)Google Scholar
  18. 18.
    Halford, G.S., Baker, R., McCredden, J.E., Bain, J.D.: How Many Variables Can Humans Process? Psychological Science 16, 70–76 (2005)CrossRefGoogle Scholar
  19. 19.
    Halford, G.S., Wilson, W.H., Phillips, S.: Processing capacity defined by relational complexity: Implications for comparative, developmental, and cognitive psychology. Behavioral and Brain Sciences 21, 803–865 (1998)Google Scholar
  20. 20.
    Casner, S., Bonar, J.: Using the expert’s diagram as a specification of expertise. In: Proceedings of IEEE Symposium on Visual Languages (1988)Google Scholar
  21. 21.
    Davies, J., Goel, A.K.: Transfer of problem-solving strategy using Covlan. Journal of Visual Languages and Computing 18, 149–164 (2007)CrossRefGoogle Scholar
  22. 22.
    Petre, M., Green, T.R.G.: Learning to Read Graphics: Some Evidence that ’Seeing’ an Information Display is an Acquired Skill. Journal of Visual Languages and Computing 4, 55–70 (1993)CrossRefGoogle Scholar
  23. 23.
    Cox, R., Brna, P.: Supporting the use of external representation in problem solving: the need for flexible learning environments. Journal of Artificial Intelligence in Education 6, 239–302 (1995)Google Scholar
  24. 24.
    Shneiderman, B.: The Eyes Have It: A Task by Data Type Taxonomy for Information Visualizations. In: Proceedings of the IEEE Conference on Visual Languages. IEEE, Los Alamitos (1996)Google Scholar
  25. 25.
    Ratwani, R.M., Trafton, J.G.: Making Graphical Inferences: A Hierarchical Framework. In: Proceedings of the Annual Meeting of the Cognitive Science Society (CogSci) (2004)Google Scholar
  26. 26.
    Ratwani, R.M., Trafton, J.G., Boehm-Davis, D.A.: Thinking Graphically: Extracting Local and Global Information. In: Proceedings of the Annual Meeting of Cognitive Science Society (2003)Google Scholar
  27. 27.
    Trafton, J.G., Kirschenbaum, S.S., Tsui, T.L., Miyamoto, R.T., Ballas, J.A., Raymond, P.D.: Turning pictures into numbers: extracting and generating information from complex visualizations. International Journal of Human-Computer Studies 53, 827–850 (2000)zbMATHCrossRefGoogle Scholar
  28. 28.
    Trafton, J.G., Trickett, S.B.: A New Model of Graph and Visualization Usage. In: Proceedings of the Annual Meeting of Cognitive Science Society (2001)Google Scholar
  29. 29.
    Heer, J., Card, S.K., Landay, J.A.: Prefuse: A Toolkit for Interactive Information Visualization. In: Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI) (2005)Google Scholar
  30. 30.
    Suo, X., Zhu, Y., Owen, G.S.: Measuring the Complexity of Visualization Design. In: Proceedings of the 2007 Workshop on Visualization for Computer Security (VizSEC) (2007)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Xiaoyuan Suo
    • 1
  • Ying Zhu
    • 1
  • Scott Owen
    • 1
  1. 1.Department of Computer ScienceGeorgia State University 

Personalised recommendations