Improving maritime anomaly detection and situation awareness through interactive visualization

Proceedings of the 11th International Conference on Information Fusion, FUSION 2008

Volumn , Issue , 2008, Pages

  Riveiro, Maria ^a   Falkman, Göran ^a   Ziemke, Tom ^a  

^a UNIVERSITY OF SKÖVDE   (Sweden)

Author keywords

Anomaly detection; Interaction; Situation awareness; Visual analytics; Visual data mining; Visualization

Indexed keywords

DATA FUSION; DECISION SUPPORT SYSTEMS; FLOW INTERACTIONS; FUSION REACTIONS; INFORMATION FUSION; INFORMATION MANAGEMENT; INTELLIGENT AGENTS; SENSOR DATA FUSION; SENSORS; SOFTWARE PROTOTYPING; VISUALIZATION;

ANOMALY DETECTION; INTERACTION; SITUATION AWARENESS; VISUAL ANALYTICS; VISUAL DATA MINING;

DATA VISUALIZATION;

EID: 56749112449     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (39)

1. N. Bomberger, B. Rhodes, M. Seibert, and A. Waxman, "Associative learning of vessel motion patterns for maritime situation awareness," in Proceedings of the 9th International Conference on Information Fusion, July 2006.
2. M. Endsley, "Toward a theory of situation awareness in dynamic systems," Human Factors Journal, vol. 37(1), pp. 32-64, 1995.
3. J. Roy, R. Breton, and S. Paradis, "Human-computer interface for the study of information fusion concepts in situation analysis and command decision support systems," in Signal Processing, Sensor Fusion, and Target Recognition X, I. Kadar, Ed., vol. 4380. SPIE, 2001, pp. 361-372.
4. B. Dasarathy, "Information fusion - what, where, why, when, and how?" Information Fusion, vol. 2, pp. 75-76, 2001.
5. M. J. Hall, S. A. Hall, and T. Tate, "Removing the HCI Bottleneck: How the Human Computer Interaction (HCI) affects the performance of Data Fusion System," in 2000 MSS National Sysmposium on Sensor and Data Fusion, 2000, pp. 89-104.
6. E. Blasch and S. Plano, "JDL level 5 fusion model: user refinement issues and applications in group tracking," in Proc. SPIE, Signal Processing, Sensor Fusion, and Target Recognition XI, I. Kadar, Ed., Jul. 2002, pp. 270-279.
7. D. Hall and S. A. H. McMullen, Eds., Mathematical Techniques in Multisensor Data Fusion, 2nd ed. Norwood, MA: Artech House, Inc., 2004.
8. M. Hall, S. Hall, and T. Tate, Removing the HCI Bottleneck: How the Human-Computer Interface (HCI) Affects the Performance of Data Fusion Systems. Boca Raton: CRC Press, 2000, ch. 19 in Handbook of multisensor data fusion.
9. E. Waltz and J. Llinas, Eds., Multisensor Data Fusion. Norwood, MA: Artech House, Inc., 1990.
10. F. González, D. Dasgupta, and R. Kozma, "Combining negative selection and classification techniques for anomaly detection," in Congress on Evolutionary Computation. IEEE, 2002, pp. 705-710.
11. D. E. Denning, "An intrusion-detection model," IEEE Transactions on Software Engineering, vol. 13, no. 2, pp. 222-232, 1987.
12. J. Kraiman, S. Arouh, and M. Webb, "Automated anomaly detection processor," in Proceedings of SPIE: Enabling Technologies for Simulation Science VI, A. Sisti and D. Trevisani, Eds., Jul 2002, pp. 128-137.
13. Y. Cai, R. Stumpf, T. Wynne, M. Tomlinson, S. H. Chung, X. Boutonnier, M. Ihmig, R. Franco, and N. Bauernfeind, "Visual transformation for interactive spatio-temporal data mining," Journal of Knowledge and Information Systems, vol. 11, no. 5, pp. 119-142, 2007.
14. F. Johansson and G. Falkman, "Detection of vessel anomlies - a Bayesian network approach," in Proceedings of the 3rd International Conference on Intelligent Sensors, Sensor Networks and Information Processing, 2007.
15. S. Musa and D. Parish, "Visualising communication network security attacks," in IV '07: Proceedings of the 11th International Conference Information Visualization. Washington, DC, USA: IEEE Computer Society, 2007, pp. 17-22.
16. I. V. Onut and A. A. Ghorbani, "A novel visualization technique for network anomaly detection," in Proceedings of the Second Annual Conference on Privacy, Security and Trust, 2004.
17. S. T. Teoh, K. L. Ma, S. F. Wu, and T. J. Jankun-Kelly, "Detecting flaws and intruders with visual data analysis," IEEE Computer Graphics and Applications, vol. 24, no. 5, pp. 27-35, 2004.
18. F. A. González, J. C. Galeano, D. A. Rojas, and A. Veloza-Suan, "Discriminating and visualizing anomalies using negative selection and self-organizing maps," in GECCO '05: Proceedings of the 2005 conference on Genetic and evolutionary computation. New York, NY, USA: ACM, 2005, pp. 297-304.
19. G. Manco, C. Pizzuti, and D. Talia, "Eureka!: an interactive and visual knowledge discovery tool," Journal of Visual Languages & Computing, vol. 15, no. 1, pp. 1-35, 2004.
20. D. A. Keim, "Information visualization and visual data mining," IEEE Transactions on Visualization and Computer Graphics, vol. 7, no. 1, pp. 1-8, 2002.
21. P. C. Wong, "Visual data mining," Computer Graphics and Applications, IEEE, vol. 19, no. 5, pp. 20-21, 1999.
22. U. Fayyad, G. G. Grinstein, and A. Wierse, Eds., Information visualization in data mining and knowledge discovery. San Francisco, CA, USA: Morgan Kaufmann Publishers Inc., 2002.
23. M. F. de Oliveira and H. Levkowitz, "From visual data exploration to visual data mining: A survey," IEEE Transactions on Visualization and Computer Graphics, vol. 9, no. 3, pp. 378-394, 2003.
24. R. Burkhard, G. Andrienko, N. Andrienko, J. Dykes, A. Koutamanis, W. Kienreich, R. Phaal, A. Blackwell, M. Eppler, J. Huang, M. Meagher, A. Grün, S. Lang, D. Perrin, W. Weber, A. Moere, B. Herr, K. Börner, J. Fekete, and D. Brodbeck, "Visualization summit 2007: ten research goals for 2010," Information Visualization, vol. 6, pp. 169-188, 2007.
25. L. Yang, "Interactive exploration of very large relational datasets through 3D dynamic projections," in KDD '00: Proceedings of the sixth ACM SIGKDD international conference on knowledge discovery and data mining. New York, NY, USA: ACM, 2000, pp. 236-243.
26. C. C. Aggarwal, "A human-computer cooperative system for effective high dimensional clustering," in KDD '01: Proceedings of the seventh ACM SIGKDD international conference on knowledge discovery and data mining. New York, NY, USA: ACM, 2001, pp. 221-226.
27. M. Ankerst, C. Elsen, M. Ester, and H.-P. Kriegel, "Visual classification: an interactive approach to decision tree construction," in KDD '99: Proceedings of the fifth ACM SIGKDD international conference on knowledge discovery and data mining. New York, NY, USA: ACM, 1999, pp. 392-396.
28. S. Kimani, S. Lodi, T. Catarci, G. Santucci, and C. Sartori, "VidaMine: a visual data mining environment," Journal of Visual Languages & Computing, vol. 15, no. 1, pp. 37-67, 2004.
29. J. Thomas and K. Cook, Eds., Illuminating the Path: The Research and Development Agenda for Visual Analytics. Los Alametos, CA: IEEE Computer Society, 2005. [Online]. Available: http://nvac.pnl.gov/agenda.stm
30. G. Andrienko, N. Andrienko, P. Jankowski, D. Keim, M. Kraak, A. MacEachren, and S. Wrobel, "Geovisual analytics for spatial decision support setting the research agenda," Journal of Geographical Information Science, vol. 21, no. 8, pp. 839-857, 2007.
31. D. Guo, "Visual analytics of spatial interaction patterns for pandemic decision support," International Journal of Geographical Information Science, vol. 21, no. 8, pp. 859-877, 2007.
32. J. Blythe, M. Patwardhan, T. Oates, M. desJardins, and P. Rheingans, "Visualization support for fusing relational, spatio-temporal data: Building career histories," in Information Fusion, 2006 9th International Conference on, Florence, Italy, 2006.
33. M. Mandiak, P. Shah, Y. Kim, and T. Kesavadas, "Development of an Integrated GUI Framework for Post-Disaster Data Fusion Visualization," in Information Fusion, 2005 8th International Conference on, vol. 2, Philadelphia, PA, USA, 2005.
34. T. Kohonen, "The Self-Organizing Map," Proceedings of the IEEE, vol. 78, no. 9, pp. 1464-1480, 1990.
35. J. B. Kraiman, S. L. Arouh, and M. L. Webb, "Automated anomaly detection processor," in Proceedings of SPIE: Enabling Technologies for Simulation Science VI, A. F. Sisti and D. A. Trevisani, Eds., Jul 2002, pp. 128-137.
36. T. Kohonen, Self-Organizing Maps, 2nd ed., ser. Springer series in information sciences. Berlin: Springer, 1997.
37. D. Gouin, P. Evdokiou, and R. Vernik, "A showcase of visualization approaches for military decision makers," in RTO IST Workshop on Massive Military Data Fusion and Visualisation: Users Talk with Developers, RTO-MP-105, Halden, Norway, 2002.
38. M. Barnes, "The human dimension of battlespace visualization: Research and design issues," Army Research Laboratory, Tech. Rep. ARL-TR-2885, February 2003.
39. H. Warston and H. Persson, "Ground surveillance and fusion of ground target sensor data in a network based defense," in Proceedings of the 7th International Conference on Information Fusion, 2004, pp. 1195-1201.