Abstract
This work proposes an attack traffic identification based on traffic properties and machine learning. Attack identification is of great importance to many areas such as: intrusion detection, security, quality of service and the development of new hardware tools related to security. For the identification of each kind of attack, statistical discriminators were used based on their power of classification. The results obtained through this technique are presented in this work.
* This work is supported by CNPq
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de Alencar Ribeiro, V.P., Filho, R.H. (2010). An Attack Classification Tool Based On Traffic Properties and Machine Learning. In: Sobh, T., Elleithy, K., Mahmood, A. (eds) Novel Algorithms and Techniques in Telecommunications and Networking. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-3662-9_54
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DOI: https://doi.org/10.1007/978-90-481-3662-9_54
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