Detecting Malicious HTTP Requests Without Log Parser Using RequestBERT-BiLSTM

Author:

Ramos Júnior Levi S.ORCID,Macêdo DavidORCID,Oliveira Adriano L. I.ORCID,Zanchettin CleberORCID

Publisher

Springer International Publishing

Reference26 articles.

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3. Chen, Z., Liu, J., Gu, W., Su, Y., Lyu, M.R.: Experience report: deep learning-based system log analysis for anomaly detection. CoRR abs/2107.05908 (2021). https://arxiv.org/abs/2107.05908

4. Du, M., Li, F., Zheng, G., Srikumar, V.: DeepLog: anomaly detection and diagnosis from system logs through deep learning, pp. 1285–1298 (2017). https://doi.org/10.1145/3133956.3134015

5. Guo, H., Yuan, S., Wu, X.: LogBERT: log anomaly detection via BERT, pp. 1–8 (2021). https://doi.org/10.1109/IJCNN52387.2021.9534113

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1. Empirical Evaluations of Machine Learning Effectiveness in Detecting Web Application Attacks;Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering;2023-12-15

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