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.
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Li, Z., Gaoa, Y., Chen, Y.: HiFIND: A high-speed flow-level intrusion detection approach with DoS resiliency. Computer Networks 54(8), 1282–1299 (2010)
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Drašar, M., Vykopal, J., Krejčí, R., Čeleda, P. (2010). Aspect-Based Attack Detection in Large-Scale Networks. In: Jha, S., Sommer, R., Kreibich, C. (eds) Recent Advances in Intrusion Detection. RAID 2010. Lecture Notes in Computer Science, vol 6307. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15512-3_27
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DOI: https://doi.org/10.1007/978-3-642-15512-3_27
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15511-6
Online ISBN: 978-3-642-15512-3
eBook Packages: Computer ScienceComputer Science (R0)