Anomaly detection enhanced classification in computer intrusion detection

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2388, Issue , 2002, Pages 186-197

  Fugate, Mike ^a   Gattiker, James R ^a  

^a LOS ALAMOS NATIONAL LABORATORY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

INTRUSION DETECTION; MERCURY (METAL); SIGNAL DETECTION; SUPPORT VECTOR MACHINES;

ANOMALY DETECTION; COMPUTER INTRUSION DETECTION; JOINT PERFORMANCE; MODELING AND PREDICTIONS; NETWORK PACKETS; SUPPORT REGIONS;

PATTERN RECOGNITION;

EID: 84958740656     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-45665-1_15     Document Type: Conference Paper

References (9)

1. Mike Fugate, James R. Gattiker, “Detecting Attacks in Computer Networks”, Los Alamos National Laboratory Technical Report, LA-UR-02-1149.
2. Richard P. Lippmann et al., “Evaluating Intrusion Detection Systems: The 1998 DARPA Off-line Intrusion Detection Evaluation”, Proc of the DARPA Information Survivability Conf., vol. 2, pp. 12-26, 1999.
3. Trevor Hastie, Robert Tibshirani, Jerome Friedman, The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Springer-Verlag, 2001.
4. Ronald Christensen (1996), Plane Answers to Complex Questions: The Theory of Linear Models, Second Edition. New York: Springer-Verlag.
5. Ronald Christensen (2001), Advanced Linear Modeling, Second Edition. New York: Springer-Verlag.
6. Bernhard Schölkopf, et al. (2000). “Estimating the Support of a High-Dimensional Distribution”, Technical report MSR-TR-99-87, Microsoft Research, Microsoft Corporation.
7. C. Chang, C. Lin,”LIBSVM: a library for support vector machines”, http://www. csie. ntu. edu. tw/ cjlin/papers/libsvm. ps. gz
8. T. Joachims, “Making large-Scale SVM Learning Practical”, Advances in Kernel Methods-Support Vector Learning, B. Schölkopf and C. Burges and A. Smola (ed.), MIT-Press, 1999.
9. M. Gokhale, D. Dubois, A. Dubois, M. Boorman,”Gigabit Rate Network Intrusion Detection Technology”, Los Alamos National Laboratory Technical Report, LAUR-01-6185.