2023 · ACM/IFIP/USENIX Middleware 2023 Industry Track

CNN-BiLSTM-Based Classification of RPL Attacks in IoT Smart Grid Networks (Industry Track)

Yue Guan | Morteza Noferesti | Naser Ezzati-Jivan

Evidence basis: metadata-only · Review status: catalog-reviewed; paper-author approval pending

iot-security deep-learning-systems machine-learning anomaly-detection

RPL attacks IoT smart grid CNN-BiLSTM routing attacks intrusion detection Middleware 2023

Core contribution: The verified record identifies this work as a Middleware 2023 industry-track paper on RPL-attack classification, but the full technical contribution was not available in the captured sources.

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BibTeX
@inproceedings{ezzatiJivan2023cnnbilstm,
  author = {Yue Guan and Morteza Noferesti and Naser Ezzati-Jivan},
  title = {CNN-BiLSTM-Based Classification of RPL Attacks in IoT Smart Grid Networks (Industry Track)},
  year = {2023},
  booktitle = {ACM/IFIP/USENIX Middleware 2023 Industry Track},
  pages = {29-34},
  publisher = {ACM},
  doi = {10.1145/3626562.3626832},
  url = {https://doi.org/10.1145/3626562.3626832}
}
Other citation formats for Word and reference managers
APA 7
Guan, Y., Noferesti, M., & Ezzati-Jivan, N. (2023). CNN-BiLSTM-Based Classification of RPL Attacks in IoT Smart Grid Networks (Industry Track). In ACM/IFIP/USENIX Middleware 2023 Industry Track (pp. 29-34). https://doi.org/10.1145/3626562.3626832
IEEE
Y. Guan, M. Noferesti, and N. Ezzati-Jivan, "CNN-BiLSTM-Based Classification of RPL Attacks in IoT Smart Grid Networks (Industry Track)," in ACM/IFIP/USENIX Middleware 2023 Industry Track, pp. 29-34, 2023, doi: 10.1145/3626562.3626832

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