Abstract
In this paper, a novel behavioral method for detection of attacks on a network is presented. The main idea is to decompose a traffic into smaller subsets that are analyzed separately using various mechanisms. After analyses are performed, results are correlated and attacks are detected. Both the decomposition and chosen analytical mechanisms make this method highly parallelizable. The correlation mechanism allows to take into account results of detection methods beside the aspect-based detection. © 2010 Springer-Verlag.
Cite
CITATION STYLE
Drašar, M., Vykopal, J., Krejčí, R., & Čeleda, P. (2010). Aspect-based attack detection in large-scale networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6307 LNCS, pp. 488–489). Springer Verlag. https://doi.org/10.1007/978-3-642-15512-3_27
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