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AutoLog: Anomaly detection by deep autoencoding of system logs., , and . Expert Syst. Appl., (2022)Assessing Invariant Mining Techniques for Cloud-Based Utility Computing Systems., , and . IEEE Trans. Serv. Comput., 13 (1): 44-58 (2020)Micro2vec: Anomaly detection in microservices systems by mining numeric representations of computer logs., , and . J. Netw. Comput. Appl., (2022)Machine Learning on Public Intrusion Datasets: Academic Hype or Concrete Advances in NIDS?, , and . DSN-S, page 132-136. IEEE, (2023)A Case Study with CICIDS2017 on the Robustness of Machine Learning against Adversarial Attacks in Intrusion Detection., , , and . ARES, page 74:1-74:8. ACM, (2023)Towards Cognitive Security Defense from Data., , and . DSN (Supplements), page 11-12. IEEE, (2019)Successful intrusion detection with a single deep autoencoder: theory and practice., , and . Softw. Qual. J., 32 (1): 95-123 (March 2024)Demystifying the role of public intrusion datasets: A replication study of DoS network traffic data., , , and . Comput. Secur., (2021)Simpler Is Better: On the Use of Autoencoders for Intrusion Detection., , and . QUATIC, volume 1621 of Communications in Computer and Information Science, page 223-238. Springer, (2022)Botnet Detection in the Internet of Things through All-in-one Deep Autoencoding., , and . ARES, page 90:1-90:7. ACM, (2022)