RT Conference Proceedings
T1 Fast predictor-corrector intrusion detection system based on clustering
A1 Petrovic, Slovodan
A1 Álvarez, Gonzalo
A1 Orfila, Agustín
A1 Carbó Rubiera, Javier Ignacio
AB A predictor-corrector intrusion detection system is proposed, whose predictors are various clustering algorithms with different initial parameters that operate in parallel on the current data set. The decisions whether abnormal behaviour is detected in the current data set are made by a number of assessors that implement various clustering quality evaluation techniques. The manager of the system estimates the quality of decision making from the pieces of information obtained a posteriori and then varies the parameters of the predictors and/or the assessors in order to achieve better overall performance of the system. In such a way, the intelligence of the system is delegated to higher decision making levels, which improves the effectiveness. Experimental results regarding the effectiveness of the system are given with the KDD CUP 1999 test data as the reference data set. These results show that very good overall performance can be achieved by selecting properly various system parameters.
PB Díaz de Santos
SN 84-7978-650-7
YR 2004
FD 2004-09
LK https://hdl.handle.net/10016/9544
UL https://hdl.handle.net/10016/9544
LA eng
NO Proceeding of: Reunión Española sobre Criptología y Seguridad de la Información (RECSI '04)Leganés, Madrid
DS e-Archivo
RD 17 jul. 2024