Title :
A comparison of input representations in neural networks: a case study in intrusion detection
Author :
Liu, Zhen ; Florez, German ; Bridges, Susan M.
Author_Institution :
Mississippi State Univ., MS, USA
fDate :
6/24/1905 12:00:00 AM
Abstract :
Recently intrusion detection techniques have shifted from user-based and connection-based to process-based approach. Forrest et al. (1996) presented one or the first papers analyzing sequences of system calls issued by a process for intrusion detection. Warrender et al. (1999) do a comparison of the accuracy and performance of different algorithms for the analysis of sequential calls. In this paper we present a comparison of two different encoding methods for three types of neural networks. We apply these classifiers to implement an anomaly detection module for UNIX processes
Keywords :
Unix; backpropagation; encoding; pattern classification; radial basis function networks; security of data; self-organising feature maps; UNIX; backpropagation; computer security; encoding; intrusion detection; neural networks; pattern classifiers; process based detection; radial basis function networks; self-organizing map networks; sequential calls; Bridges; Computer aided software engineering; Databases; Encoding; Hidden Markov models; Intelligent networks; Internet; Intrusion detection; Neural networks; TCPIP;
Conference_Titel :
Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-7278-6
DOI :
10.1109/IJCNN.2002.1007775
