A Controversial Study on Random Forest Accuracy for Attack Detection
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-47451-4_41
Reference12 articles.
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3. Ahmad, Z., Khan, A.S., Shiang, C.W., Abdullah, J., Ahmad, F.: Network intrusion detection system: a systematic study of machine learning and deep learning approaches. Trans. Emerg. Telecommun. Technol. 32(1), e4150 (2021)
4. Kelton, A.P., da Costa, J., Celso, O., Munoz, R., de Albuquerque, C.: Internet of Things: a survey on machine learning-based intrusion detection approaches. Comput. Netw. 151, 147–157 (2019)
5. Laghrissi, F., Douzi, S., Douzi, K., Hssina, B.: Intrusion detection systems using Long Short-Term Memory (LSTM). J. Big Data 8, 65 (2021)
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