Traffic classification has always been a fundamental aspect regarding the identification of appli... more Traffic classification has always been a fundamental aspect regarding the identification of applications on the network that has allowed to apply different actions or services depending on their type, such as best-effort delivery or discarding the traffic in case of a malicious application. The constant growth of the internet and the relentless pace of change on the applications have made traditional methods no longer feasible. Nonetheless, the application of machine learning methods has gathered strength over time. In this thesis, we analyze different algorithms with the aim to obtain a good classifier and design a solution capable of achieving an acceptable performance when identifying malware traffic in a real-time environment using the information provided by Netflow protocol.
Traffic classification has always been a fundamental aspect regarding the identification of appli... more Traffic classification has always been a fundamental aspect regarding the identification of applications on the network that has allowed to apply different actions or services depending on their type, such as best-effort delivery or discarding the traffic in case of a malicious application. The constant growth of the internet and the relentless pace of change on the applications have made traditional methods no longer feasible. Nonetheless, the application of machine learning methods has gathered strength over time. In this thesis, we analyze different algorithms with the aim to obtain a good classifier and design a solution capable of achieving an acceptable performance when identifying malware traffic in a real-time environment using the information provided by Netflow protocol.
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Papers by Hien Nguyen