Role of Soft Outlier Analysis in Database Intrusion Detection

Author:

Brahma Anitarani,Panigrahi Suvasini

Publisher

Springer Singapore

Reference14 articles.

1. Mathew, S., Petropoulos, M., Ngo, H.Q., Upadhyaya, S.: A data-centric approach to insider attack detection in database systems. LNCS 6307, 382–401 (2010)

2. Abadeh, M.S., Habibi, J., Lucas, C.: Intrusion detection using a fuzzy genetics-based learning algorithm. J. Netw. Comput. Appl. 30, 414–428 (2007)

3. Christina, Y.C., Michael, G., Karl, L.: DEMIDS: a misuse detection system for database systems. In: Proceedings of the Third Annual IFIP TC-11 WG 11.5 Working Conference on Integrity and Internal Control in Information Systems, pp. 158–178. Amsterdam, Netherlands (1999)

4. Lee, S.Y., Low, W.L., Wong, P. R.: Learning fingerprints for a database intrusion detection system. In: ESORICS 2002. Lecture Notes in Computer Science, No. 2502, pp. 264–280. Springer (2002)

5. Christina, Y.C., Michael, G., Karl, L.: Demids: a misuse detection system for database systems. In: Third International IFIP TC-11 WG11.5 Working Conference on Integrity and Internal Control in Information Systems, pp. 159–178 (1999)

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