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An Empirical Study on Flow-based Botnet Attacks Prediction



Mitsuhiro Hatada, Matthew A. Scholl


In the era of the Internet of Things, botnet threats are rising, which has prompted many studies on botnet detection and measurement. In contrast, this study aims to predict botnet attacks, such as massive spam emails and distributed denial-of-service attacks. To that end, this empirical study presents a prediction method for botnet attacks. The method leverages measurement of command and control (C2) activities and automated labeling by associating C2 with attacks. The method was evaluated using a large-scale, real-world, and long-term dataset. The result shows that the proposed method can predict an increase in attacks with an accuracy of 0.767. The contribution to prediction was further analyzed in terms of features and time.
Technical Note (NIST TN) - 2111
Report Number


Attack prediction, botnet, command and control, LSTM


Hatada, M. and Scholl, M. (2020), An Empirical Study on Flow-based Botnet Attacks Prediction, Technical Note (NIST TN), National Institute of Standards and Technology, Gaithersburg, MD, [online], (Accessed May 21, 2024)


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Created October 21, 2020, Updated October 27, 2020