Evaluating a Deep Learning Model for Cyberattack Detection Based on Network Traffic
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-60725-7_1
Reference20 articles.
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3. Afek, Y., Bremler-Barr, A., Feibish, S.L.: Zero-day signature extraction for high-volume attacks. IEEE/ACM Trans. Netw. 27(2), 691–706 (2016). https://doi.org/10.1109/TNET.2019.2899124
4. Wang, R., Jia, Z., Ju, L.: An entropy-based distributed DDoS detection mechanism in software-defined networking. In: 2015 IEEE Trustcom/BigDataSE/ISPA, pp. 310–317, IEEE, Helsinki, Finland (2015). https://doi.org/10.1109/Trustcom.2015.389
5. Wang, X., Chen, M., Xing, C., Zhang, T.: Defending DDoS attacks in software-defined networking based on legitimate source and destination IP address database. IEICE Trans. Inf. Syst. 99(4), 850–859 (2016). https://doi.org/10.1587/transinf.2015ICP0016
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