A high-performance network intrusion detection system
CCS '99 Proceedings of the 6th ACM conference on Computer and communications security
Bro: a system for detecting network intruders in real-time
Computer Networks: The International Journal of Computer and Telecommunications Networking
Windows Sockets Network Programming
Windows Sockets Network Programming
Fusion of multiple classifiers for intrusion detection in computer networks
Pattern Recognition Letters
The BSD packet filter: a new architecture for user-level packet capture
USENIX'93 Proceedings of the USENIX Winter 1993 Conference Proceedings on USENIX Winter 1993 Conference Proceedings
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The Intrusion Detection System (IDS) is generally used the misuse detection model based on rules because this model has low false alarm rates. However, the rule based IDSs are not efficient for mutated attacks, because they need additional rules for the variations of the attacks. In this paper, we propose an intrusion detection system using the Principal Component Analysis (PCA) and the Time Delay Neural Network (TDNN). Packets on the network can be considered as gray images of which pixels represent bytes of the packets. From these continuous packet images, we extract principal components. And these components are used as an input of a TDNN classifier that discriminates between normal and abnormal packet flows. The system deals well with various mutated attacks, as well as well-known attacks.