A data mining approach for database intrusion detection

Proceedings of the ACM Symposium on Applied Computing

Volumn 1, Issue , 2004, Pages 711-716

  Hu, Yi ^a   Panda, Brajendra ^a  

^a 3202 Bell Engineering Center   (United States)

Author keywords

Data Mining; Database Security; Intrusion Detection

Indexed keywords

CODES (SYMBOLS); COMPUTER SYSTEMS; DATA MINING; DATA REDUCTION; INFORMATION ANALYSIS; MATHEMATICAL MODELS; SECURITY OF DATA; SYSTEMS ANALYSIS; WORLD WIDE WEB;

CRITICAL COMPUTER SYSTEMS; DATABASE INTRUSION; DATABASE SECURITY; INTRUSION DETECTION;

DATABASE SYSTEMS;

EID: 2442430540     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/967900.968048     Document Type: Conference Paper

References (16)

1. Agrawal, R. and Srikant, R. Mining Sequential Patterns. In Proceedings of the 1995 Int. Conf. Data Engineering, Taipei, Taiwan, March 1995. Pages 3-14.
2. Barbara, D., Goel, R., and Jajodia, S. Mining Malicious Data Corruption with Hidden Markov Models, In Proceedings of the 16th Annual IFIP WG 11.3 Working Conference on Data and Application Security, Cambridge, England, July 2002.
3. Chung, C., Gertz M., and Levitt, K. DEMIDS: A Misuse Detection System for Database Systems. In Third Annual IFIP TC-11 WG 11.5 Working Conference on Integrity and Internal Control in Information Systems, Kluwer Academic Publishers, pages 159-178, November 1999.
4. Codd, E. A Relational Model for Large Shared Data Banks. In Communications of ACM, June 1970.
5. Fawcett, T. and Provost F. Adaptive Fraud Detection. Data Mining and Knowledge Discovery, pages 177-181, 1997
6. Forrest, S., Hofmeyr, S. A., Somayaji, A., and Longstaff, T. A. A Sense of Self for Unix Processes. In Proceedings of the 1996 IEEE Symposium on Security and Privacy, pages 120-128, IEEE Computer Society Press, 1996
7. Frank, J. Artificial Intelligence and Intrusion Detection: Current and Future Directions. In Proceedings of the 17th National Computer Security Conference, October 1994.
8. Heady, R., Luger, G., Maccabe, A., and Servilla, M. The Architecture of a Network Level Intrusion Detection System. Technical report, Computer Science Department, University of New Mexico, August 1990.
9. Javitz, H. S. and Valdes, A. The SRI IDES Statistical Anomaly Detector. In Proceedings of the IEEE Symposium on Security and Privacy, May 1991
10. Lee, W., Nimbalkar, R.A., Yee, K.K., Patil, S.B., Desai, P.H., Tran, T.T., and Stolfo, S.J. A Data Mining and CIDF Based Approach for Detecting Novel and Distributed Intrusions. In Proceedings of 3rd International Workshop on the Recent Advances in Intrusion Detection, October 2000.
11. Lee, V. C.S., Stankovic, J. A., Son, S. H. Intrusion Detection in Real-time Database Systems Via Time Signatures. In Proceedings of the Sixth IEEE Real Time Technology and Applications Symposium, 2000.
12. Lee, W. and Stolfo S. Data Mining Approaches for Intrusion Detection. In USENIX Security Symposium, 1998.
13. Liu, P., Ammann, P., and Jajodia, S. Rewriting Histories: Recovering from Malicious Transactions. In Distributed and Parallel Databases, Vol. 18, No. 1, pages 7-40, January 2000.
14. Pei, J., Han, J., Pinto, H., Chen, Q, Dayal, U., and Hsu, M-C. PrefixSpan: Mining Sequential Patterns Efficiently by Prefix-Projected Pattern Growth. In Proceeding of 2001 International Conference on Data Engineering (ICDE'01), Heidelberg, Germany, April 2001.
15. Sobhan, R. and Panda, B. Reorganization of Database Log for Information Warfare Data Recovery. In Proceedings of the 15th Annual IFIP WG 11.3 Working Conference on Database and Application Security, July 2001.
16. Srikant, R. and Agrawal, R. Mining Sequential Patterns: Generalizations and Performance Improvements. In EDBT, pages 3-17, March 1996