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English Information

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Authors
# Name
1 Osvaldo Sebastião(osvalnunes@usp.br)
2 Leonardo Grupioni(leogrupioni@usp.br)
3 Mateus Calado(padoca@padoca.org)
4 José Eduardo(zedududas1973@gmail.com)
5 Felipe Valencia de Almeida(fvalencia@usp.br)
6 Jorge Júnior(jorgerady@usp.br)

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Reference
# Reference
1 Almeida, F., Quille, R., Monteiro, D., Freitas, L., and Correa, P. (2025). Análise de IA explicável na detecção de gases nos solos. In Anais do XIX Brazilian e-Science Workshop, pages 121–128, Porto Alegre, RS, Brasil. SBC. DOI: 10.5753/bresci.2025.248241.
2 Arreche, O., Guntur, T. R., Roberts, J. W., and Abdallah, M. (2024). E-XAI: Evaluating black-box explainable AI frameworks for network intrusion detection. IEEE Access, 12:23954–23988. DOI: 10.1109/ACCESS.2024.3365140.
3 Chen, Z., Li, Z., Huang, J., Liu, S., and Long, H. (2024). An effective method for anomaly detection in industrial Internet of Things using XGBoost and LSTM. Scientific Reports, 14:23969. DOI: 10.1038/s41598-024-74822-6.
4 Hasan, T. and Tasnim, S. (2025). Real-time explainable IoT security with machine learning and CTGAN-enhanced detection for resource-constrained devices. Ad Hoc Networks, 178:103937. DOI: 10.1016/j.adhoc.2025.103937.
5 Kumar, D., Ramaswamy, S., and Patel, J. (2024). An experimental comparison and impact analysis of various RPL-based IoT security threats using Contiki simulator. In 2024 IEEE International Conference on Communication Systems and Networks (COMSNETS), pages 1–7. IEEE. DOI: 10.1109/COMSNETS59351.2024.10427337.
6 Nishanth, N. and Mujeeb, A. (2021). Modeling and detection of flooding-based denial of service attacks in wireless ad hoc networks using uncertain reasoning. IEEE Transactions on Cognitive Communications and Networking, 7(3):893–904. DOI: 10.1109/TCCN.2021.3055503.
7 Pandey, V. K., Prakash, S., Gupta, T. K., Sinha, P., et al. (2025). Enhancing intrusion detection in wireless sensor networks using a Tabu search based optimized random forest. Scientific Reports, 15:18634. DOI: 10.1038/s41598-025-03498-3.
8 Pandey, V. K., Prakash, S., Gupta, T. K., Sinha, P., et al. (2025). Enhancing intrusion detection in wireless sensor networks using a Tabu search based optimized random forest. Scientific Reports, 15:18634. DOI: 10.1038/s41598-025-03498-3.
9 programmer3 (2026). Trust-Aware IIoT Routing Dataset. Kaggle dataset. Disponível em: https://www.kaggle.com/datasets/programmer3/trust-aware-iiot-routing-dataset. Acesso em: 8 maio 2026.
10 Rahman, M. M., Shakil, S. A., and Mustakim, M. R. (2025). A survey on intrusion detection system in IoT networks. Cyber Security and Applications, 3:100082. DOI: 10.1016/j.csa.2024.100082.