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Network Traffic Classification is the crucial area in the field of smart city. As in the smart city a lot of data flow is generated using IoT systems. These net-flows need to be categories in normal and attack category in order to deal with the network attacks. In this paper, we have used the recent NF-TON-IOT-V2 dataset which contains recent attacks. NF-TON-IOT-V2 is the net-flow adaptation of the original TON-IOT dataset. Our research is intended to classify the flows in the Benign and Attack category. To do this intended task, we have used binary classification and implemented a decision tree classifier. Our proposed model gives 99.31% accuracy.

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Detecting Network Attacks Using Decision Tree Classifier

  • 会议论文

  • 发表日期：

    2026年

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  • Sujata N. Bhosle,
  • Jayshri Pagare

摘要

Network Traffic Classification is the crucial area in the field of smart city. As in the smart city a lot of data flow is generated using IoT systems. These net-flows need to be categories in normal and attack category in order to deal with the network attacks. In this paper, we have used the recent NF-TON-IOT-V2 dataset which contains recent attacks. NF-TON-IOT-V2 is the net-flow adaptation of the original TON-IOT dataset. Our research is intended to classify the flows in the Benign and Attack category. To do this intended task, we have used binary classification and implemented a decision tree classifier. Our proposed model gives 99.31% accuracy.