The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Machine Learning Based IoT Intrusion Detection System: An MQTT Case Study (MQTT-IoT-IDS2020 Dataset)
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Hosmer, D. W., Lemeshow, S., & Sturdivant, R. X. (2013) · Wiley Series in Probability and Statistics · doi:10.1002/9781118548387 · Cited by 13,861
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Ullah, I., & Mahmoud, Q. H. (2022) · IEEE Access · doi:10.1109/access.2022.3176317 · Cited by 270
Bhandari, G., Lyth, A., Shalaginov, A., & Grønli, T.-M. (2023) · Electronics · doi:10.3390/electronics12020298 · Cited by 79
A Systematic Review of Data-Driven Attack Detection Trends in IoT
Haque, S., El-Moussa, F., Komninos, N., & Muttukrishnan, R. (2023) · Sensors · doi:10.3390/s23167191 · Cited by 38
Enhancing Critical Infrastructure Security: Unsupervised Learning Approaches for Anomaly Detection
Pinto, A., Herrera, L.-C., Donoso, Y., & Gutierrez, J. A. (2024) · International Journal of Computational Intelligence Systems · doi:10.1007/s44196-024-00644-z · Cited by 35
Lightweight Identification of Malicious IoT Traffic via Cross-View Knowledge Distillation
Nie, F., Liu, W., Liu, G., Gao, B., Huang, J., & Yuen, C. (2025) · IEEE Internet of Things Journal · doi:10.1109/jiot.2025.3596167 · Cited by 1
Metadata
- Authors
- Hindy, H., Bayne, E., Bures, M., Atkinson, R., Tachtatzis, C., & Bellekens, X.
- Venue
- Lecture Notes in Networks and Systems
- Publisher
- Springer International Publishing
- Published
- 2021
- Pages
- 73-84
- ISSN
- 2367-3370 (ISSN-L)
- 2367-3389
- OpenAlex
- W3096448935
- Cited by
- 198
- References
- 1
- FWCI
- 29.83
- Type
- conference paper
- Language
- en
- Open access
- green
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- The paper
- Hindy, H., Bayne, E., Bures, M., Atkinson, R., Tachtatzis, C., & Bellekens, X. (2021). Machine Learning Based IoT Intrusion Detection System: An MQTT Case Study (MQTT-IoT-IDS2020 Dataset). Lecture Notes in Networks and Systems. https://doi.org/10.1007/978-3-030-64758-2_6
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.