Anomaly, novelty, one-class classification: A short introduction

2010 International Conference on Computer Information Systems and Industrial Management Applications, CISIM 2010

Volumn , Issue , 2010, Pages 1-6

  Bartkowiak, Anna M ^a  

^a UNIVERSITY OF WROC AW   (Poland)

Author keywords

Anomaly detection; Intrusion detection; Object classification and recognition; One class classification; Schonlau's masquerade data

Indexed keywords

ANOMALY DETECTION; ARE BORING; CREDIT CARDS; DATA ANALYSIS; LEGITIMATE USERS; NORMAL STATE; OBJECT CLASSIFICATION; OBSERVED DATA; OFF-SHORE; OIL PLATFORMS; ONE-CLASS CLASSIFICATION; SCHONLAU'S MASQUERADE DATA;

DECISION MAKING; DRILLING PLATFORMS; FAULT DETECTION; INDUSTRIAL MANAGEMENT; INFORMATION SYSTEMS; PROJECT MANAGEMENT;

INTRUSION DETECTION;

EID: 78651225286     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CISIM.2010.5643699     Document Type: Conference Paper

References (34)

1. V. Barnett and T. Lewis, Outliers in Statistical Data, 3rd ed., Chichester: Wiley, 1994.
2. A. Bartkowiak, "Outliers in some Faces and nonFaces data", Int. J. of Biometrics, Vol. 2, No. 1, 2010, pp. 2-18.
3. A. Bartkowiak, "Outliers in biometrical data, what's old, what's new", Int. J. of Biometrics, Vol. 2, No. 3, 2010, pp. 203-221
4. A. Bartkowiak and J. Zdziarek: "Outliers: a continuing problem". Bulletin of the International Statistical Institute, 54th Session, Proceedings. Berlin August 2003. http://isi.cbs.nl/iamamember/CD3/ index.html
5. A. Bartkowiak and A. Szustalewicz, "Outliers - finding and classifying which genuine and which spurious", Computational Statistics, vol. 15, no 1, 2000, pp. 3-12.
6. R.A. Becker, C. Volinsky, and A.R. Wilks, "Fraud detection in telecommunications: History and lessons learnt", Technometrics, February 2010, vol. 52, No. 1, pp. 20-33.
7. C.M. Bishop, "Novelty detection and neural network validation". Proceedins of IEE Conference on Vision and Image Signal Processing, 1994, pp. 217-222.
8. H.S. Burkom, S.P. Murphy,and G. Shmueli, "Automated time series forcasting for biosurveillance", Statistics in Medicine, vol. 26, 2007, pp. 4202-4218.
9. U.G. Daphne et al., "Algorithm for statistical detection of peaks - syndromic surveillance system for the Athens 2004 Olympic Games". MMWR, September 24, 2004, pp. 36-94.
10. D. DasGupta, S. Yu, and N.S. Majumdar, "MILA - Multilevel immune learning algorithm", Gecco 2003, LNCS 2723, pp. 183-194.
11. D. Dasgupta and S. Forrest, "Artificial immune systems in industrial applications", Proc. IPMM, IEEE Press, 1999, pp. 257-267,
12. R.P.W. Duin et al., PRTools4, A Matlab Toolbox for Pattern Recognition, Version 4.1, August 2007, Delft Pattern Recognition Research, Faculty EWI - ICT, Delft University of Technology, Delft The Netherlands, http://www.prtools.org
13. S. Forrest, A.S. Perelson, L. Allen, and R. Cherukuri, "Self - nonself discrimination in a computer", Proc. of the 1994 IEEE Symposium on Research in Security and Privacy, IEEE Press, Los Alamitos, CA, 1994, pp. 202-212.
14. D.J. Hand, "Fraud detection in telecommunications and banking: Discussion of Becker, Volinsky, and Wilks (2010) and Sudjianto et al. (2010)", Technometrics, Vol. 52, No. 1, 2010, pp. 34-38.
15. V.J. Hodge and J. Austin, "A Survey of Outlier Detection Metodologies", Artificial Intelligence Review, Kluwer Academic Publishers, Vol. 22, 2004, 85-124.
16. M. Markou and S. Singh, "Novelty detection: a review - Part 1: statistical approaches", Signal Processing, Vol. 83, 2003, pp. 2481-2497.
17. "Part 2: Neural network based approaches", Signal Processing, Vol. 83, 2003, pp. 2499-2521.
18. S. Marsland, U. Nehmzow, and J. Shapiro, "On-line novelty detection for autonomous mobile robots". Robotics and Autonomous Systems Vol. 51, 2005, pp. 191-2006.
19. M.E. Otey, A. Ghoting, and S. Parthasarathy, "Fast distributed outlier detection in mixed-attribute data sets", Data Mining and Knowledge Discovery, Vol. 12, 2006, pp. 203-228.
20. A. Patcha and J-M Park, "An overview of anomaly detection techniques: Existing solutions and latest technology trends", Computer Networks, Vol. 51, 2007, pp. 3448-3470.
21. D. Pelleg, "Scalable and Practical Probability Density Estimators for Scientific Anomaly Detection". PhD Thesis. CMU Pittsbourg 2004.
22. E. Pȩkalska and R.P.W. Duin, The Dissimilarity Representation for Pattern Recognition. Foundations and Applications. World Scientific, Singapore, December 2005.
23. E. Pȩkalska, M. Skurichina and R.P.W. Duin, "Combining dissimilarity-based one-class classifier", MCS 2004, LNCS 3077, Springer Berlin Heidelberg 2004, pp. 122-133.
24. T. Rowan, "Negotiating WIFI security", Network Security, February 2010, pp. 8-12.
25. M. Schonlau, Masquerading used data, web page at: http://www.schonlau.net
26. M. Schonlau, et al., "Computer intrusion: Detecting Masquerades", Statistical Science, Vol. 16, 2001, pp. 1-17.
27. A. Sudjianto, et al., "Statistical methods for fighting financial crimes", Technometrics, Vol. 52, No. 1, 2010, pp. 5-19.
28. G. Shmueli and H. Burkom, "Statistical challenges facing early outbreak detection in biosurveillance", Technometrics, Vol. 52, No. 1, 2010, pp. 39-51.
29. C. Surace and K. Worden, "Novelty detection in a changing environment: A negative selection approach", Mechanical Systems and Signal Processing, Vol. 24, 2010, pp. 1114-1128.
30. D.M.J. Tax, "One-class classification", PhD dissertation, Delft University of Technology, 2001, available at: http://www-ict.ewi.tudelft.nl/ papers.html
31. D.M.J. Tax, "Data description toolbox dd-tools 1.6.3. A Matlab toolbox for data description, outlier and novelty detection", EWI, Delft UT, Sept 2008.
32. S.T. Wierzchon, Artificial Immunological Systems (in Polish), Akademicka Oficyna Wydawnicza Exit, Warsaw 2001.
33. M. Ye, X. Li, and M.E. Orlowska, "Projected outlier detection in high-dimensional mixed attributes data set", Expert Systems with Applications Vol. 36, 2009, pp. 7104-7113.
34. A. Ypma, "Learning methods for machine vibration analysis and health monitoring", PhD dissertation, Faculty EWI, Delft University of Technology, 2001, http://www-ict.ewi.tudelft.nl/papers.html