Conformal prediction for distribution-independent anomaly detection in streaming vessel data

Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Volumn , Issue , 2010, Pages 47-55

  Laxhammar, Rikard ^a,b   Falkman, Göran ^a  

^a UNIVERSITY OF SKÖVDE   (Sweden)

^b Saab AB   (Sweden)

Author keywords

Anomaly detection; Conformal prediction; Sea surveillance

Indexed keywords

ANOMALY DETECTION; APPLICATION SPECIFIC; CONFIDENCE LEVELS; CONFORMAL PREDICTION; EMPIRICAL ERRORS; FALSE ALARMS; NOVEL APPLICATIONS; ONLINE LEARNING; SEA SURVEILLANCE; TRAINING DATA; UPPER BOUND;

DATA COMMUNICATION SYSTEMS; DATA MINING; HYDRAULICS; MONITORING; TECHNICAL PRESENTATIONS;

FORECASTING;

EID: 77956247958     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1833280.1833287     Document Type: Conference Paper

References (15)

1. C. Brax, L. Niklasson, and M. Smedberg. Finding behavioral anomalies in public areas using video surveillance data. In Proceedings of the 11th International Conference on Information Fusion, Cologne, Germany, July 2008.
2. V. Chandola, A. Banerjee, and V. Kumar. Anomaly detection: A survey. ACM Comput. Surv., 41(3):1-58, 2009.
3. DARPA/IXO. Predictive analysis for naval deployment activities (panda) proposal information package, 2005.
4. E. Eskin. Anomaly detection over noisy data using learned probability distributions. In Proceedings of the International Conference on Machine Learning, 2000.
5. A. Gammerman and V. Vovk. Hedging predictions in machine learning. Computer Journal, 50(2):151-163, 2007.
6. D. Hawkins. Identification of Outliers. Chapman and Hall, London, 1980.
7. F. Johansson and G. Falkman. Detection of vessel anomalies - a bayesian network approach. In Proceedings of 3rd International Conference on Intelligent Sensors, Sensor Networks and Information Processing, 2007.
8. R. Laxhammar. Anomaly detection for sea surveillance. In Proceedings of the 11th International Conference on Information Fusion, pages 1-8, Cologne, Germany, July 2008.
9. R. Laxhammar, G. Falkman, and E. Sviestins. Anomaly detection in sea traffic - a comparison of the gaussian mixture model and the kernel density estimator. In Proceedings of the 12th International Conference on Information Fusion, pages 756-763, Seattle, USA, July 2009.
10. B. Rhodes, N. Bomberger, M. Seibert, and A. Waxman. Maritime situation monitoring and situation awareness using learning mechanisms. In Proceedings of the Military Communications Conference 2005, Atlantic City, NJ, USA, October 2005.
11. B. Ristic, B. La Scala, M. Morelande, and N. Gordon. Statistical analysis of motion patterns in ais data: Anomaly detection and motion prediction. In Proceedings of the 11th International Conference on Information Fusion, Cologne, Germany, July 2008.
12. J. Roy. Anomaly detection in the maritime domain. In C. S. Halvorson, D. Lehrfeld, and T. T. Saito, editors, Proceedings of the SPIE Optics and Photonics in Global Homeland Security IV, volume 6945, Orlanda, USA, March 2008.
13. B. Schölkopf, R. Williamson, A. Smola, J. Shawe-Taylor, and J. Platt. Support vector method for novelty detection. In Advances in Neural Information Processing Systems, volume 12, 2000.
14. G. Shafer and V. Vovk. A tutorial on conformal prediction. J. Mach. Learn. Res., 9:371-421, 2008.
15. V. Vovk, A. Gammerman, and G. Shafer. Algorithmic Learning in a Random World. Springer-Verlag New York, Inc., Secaucus, NJ, USA, 2005.