Abstract
With the rapid growth of the distributed denial of service (DDoS) attacks, the identification and detection of attacks has become a crucial issue. In this paper we present a neural network approach to detecting the DDoS attacks towards the domain name system. A multi-layer feed-forward neural network is employed as a classifier based on the selected features that reflect the characteristics of DDoS attacks. The performance and the computational efficiency of the neural network classifier are both evaluated.
This research is supported by the China Next Generation Internet Project: Industrialization of Next Generation Trusted Domain Name Service System (Grant number: CNGI-09-03-04).
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Wu, J., Wang, X., Lee, X., Yan, B. (2010). Detecting DDoS Attack towards DNS Server Using a Neural Network Classifier. In: Diamantaras, K., Duch, W., Iliadis, L.S. (eds) Artificial Neural Networks – ICANN 2010. ICANN 2010. Lecture Notes in Computer Science, vol 6354. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15825-4_15
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DOI: https://doi.org/10.1007/978-3-642-15825-4_15
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