ARCHIVES

1. Luo, J., & Bridges, S. M. (2000). Mining fuzzy association rules and fuzzy frequency episodes for intrusion detection. International
Journal of Intelligent Systems, 15(8), 687-704.
2. Mukkamala, S., Sung, A. H., & Abraham, A. (2005). Intrusion detection using ensemble of soft computing paradigms. In
Computational Intelligence in Information Assurance and Security (pp. 239-267). Springer, Berlin, Heidelberg.
3. Cannady, J. (1998). Artificial neural networks for misuse detection. Proceedings of the 1998 National Information Systems Security
Conference (NISSC).
4. Amor, N. B., Benferhat, S., & Elouedi, Z. (2004). Naive Bayes vs decision trees in intrusion detection systems. Proceedings of the
2004 ACM symposium on Applied computing, 420-424.
5. Hofmeyr, S. A., Forrest, S., & Somayaji, A. (1998). Intrusion detection using sequences of system calls. Journal of Computer Security, 6(3), 151-180.
6. Sundaram, A. (1996). An introduction to intrusion detection. ACM Crossroads, 2(4es), 3.
7. Lee, W., Stolfo, S. J., & Mok, K. W. (1998). Mining audit data to build intrusion detection models. Proceedings of the Fourth
International Conference on Knowledge Discovery and Data Mining, 66-72.
8. Ghosh, A. K., Schwartzbard, A., & Schatz, M. (1999). Learning program behavior profiles for intrusion detection. Proceedings of
the 1st USENIX workshop on Intrusion Detection and Network Monitoring, 51-62.
9. Bridges, S. M., & Vaughn, R. B. (2000). Fuzzy data mining and genetic algorithms applied to intrusion detection. Proceedings
of the 23rd National Information Systems Security Conference (NISSC), 16-19.
10. Debar, H., Becker, M., & Siboni, D. (1992). A neural network component for an intrusion detection system. Proceedings of the 1992
IEEE Symposium on Research in Security and Privacy, 240-250.
11. Crosbie, M., & Spafford, E. (1995). Applying genetic programming to intrusion detection. Proceedings of the AAAI Fall Symposium
on Genetic Programming1-8.,
12. Warrender, C., Forrest, S., & Pearlmutter, B. (1999). Detecting intrusions using system calls: Alternative data models. Proceedings
of the 1999 IEEE Symposium on Security and Privacy, 133-145.
13. Lane, T., & Brodley, C. E. (1997). An application of machine learning to anomaly detection. Proceedings of the 20th National
Information Systems Security Conference (NISSC), 366-380.
14. Anderson, J. P. (1980). Computer security threat monitoring and surveillance. Technical Report, James P. Anderson Company.
15. Lee, W., & Xiang, D. (2001). Information-theoretic measures for anomaly detection. Proceedings of the 2001 IEEE Symposium on
Security and Privacy, 130- 143.
16. Eskin, E., Arnold, A., Prerau, M., Portnoy, L., & Stolfo, S. J. (2002). A geometric framework for unsupervised anomaly detection:
Detecting intrusions in unlabeled data. Applications of Data Mining in Computer Security, 77-101.
17. Zhang, Y., & Paxson, V. (2000). Detecting stepping stones. Proceedings of the 9th USENIX Security Symposium, 171-184.
18. Mahoney, M. V., & Chan, P. K. (2003). An analysis of the 1999 DARPA/Lincoln Laboratory evaluation data for network anomaly
detection. Proceedings of the Sixth International Symposium on Recent Advances in Intrusion Detection (RAID), 220-237.
19. Kruegel, C., Mutz, D., Robertson, W., & Vigna, G. (2003). Bayesian event classification for intrusion detection. Proceedings of the
19th Annual Computer Security Applications Conference, 14-23.
20. Axelsson, S. (1999). Research in intrusion-detection systems: A survey. Technical Report, Department of Computer Engineering,
Chalmers University of Technology.
21. Debar, H., Dacier, M., & Wespi, A. (2000). A revised taxonomy for intrusion-detection systems. Annals of Telecommunications,
55(7-8), 361-378.
22. Mukherjee, B., Heberlein, L. T., & Levitt, K. N. (1994). Network intrusion detection. IEEE Network.
23. Staniford, S., Hoagland, J., & McAlerney, J. (2002). Practical automated detection of stealthy portscans. Journal of Computer
Security, 10(1-2), 105-136.
24. Denning, D. E. (1987). An intrusion-detection model. IEEE Transactions on Software Engineering, SE-13(2), 222-232.
25. Anderson, D., Lunt, T. F., Javitz, H., Tamaru, A., & Valdes, A. (1995). Detecting unusual program behavior using the statistical
component of the next-generation intrusion detection expert system (NIDES). Technical Report, Computer Science Laboratory, SRI
International.
26. Kemmerer, R. A., & Vigna, G (2002). Intrusion detection: a brief history and overview. Computer, 35(4), 27-30.
27. Liao, Y., & Vemuri, V. R. (2002). Use of k-nearest neighbor classifier for intrusion detection. Computers & Security, 21(5), 439-448.
28. Vigna, G., & Kemmerer, R. A. (1999). NetSTAT: A network-based intrusion detection approach. Proceedings of the 14th Annual
Computer Security Applications Conference, 25-34.