Title :
Piecewise classification of attack patterns for efficient network intrusion detection
Author :
Zaidi, Abdelhalim ; Agoulmine, Nazim ; Kenaza, Tayeb
Author_Institution :
LRSM Group, CNRS IBISC Lab, Evry Val d´´Essonne University, Evry, France
Abstract :
This paper presents a new scheme to improve the efficiency of pattern matching algorithms. The proposed approach is based on a piecewise classification of patterns using the common substrings. The main idea is to split the whole set of patterns into small subsets in accordance to the common substrings and treat the subsets independently. To reduce the number of patterns to match, we use the common substrings as an index for the search. We show that are our algorihtm is capable to outcome in term of performance other reference algorithms, such as Aho-Corasick.
Keywords :
Algorithm design and analysis; Classification algorithms; Engines; Heuristic algorithms; Intrusion detection; Pattern matching; Servers; Common substrings; Intrusion Detection; String classification; String matching;
Conference_Titel :
Security and Cryptography (SECRYPT), Proceedings of the 2010 International Conference on
Conference_Location :
Athens