Detecção de Anomalias e Falhas em Redes LoRa Mesh: Uma Abordagem com Isolation Forest e LLM para Redução de Falsos Positivos
Resumo
Redes LoRa Mesh para Internet das Coisas (IoT) enfrentam falhas físicas e instabilidade topológica. Nestes cenários, a variabilidade do canal sem fio e reconvergências benignas elevam os falsos positivos no monitoramento, causando fadiga de alertas. Este artigo propõe uma arquitetura de detecção composta por três camadas: (i) triagem não supervisionada via Isolation Forest, (ii) tipificação por regras determinísticas e (iii) validação semântica com Large Language Model (LLM). Avaliada em um testbed real, a integração do LLM como filtro contextual suprimiu autonomamente 89,1% dos falsos alertas originados pelo modelo estatístico. A solução garantiu a notificação ininterrupta de anomalias críticas por meio de mecanismos de degradação controlada.
Referências
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Augustin, A., Yi, J., Clausen, T. and Townsley, W. M. (2016) "A Study of LoRa: Long Range & Low Power Networks for the Internet of Things", Sensors, vol. 16, no. 9, p. 1466.
Balanis, C. A. (2016) Antenna Theory: Analysis and Design, 4th ed., Wiley, Hoboken, NJ, USA.
Bonanno, M., Russo, M., Santoro, C., Santoro, F. F. and Tudisco, A. (2025) "BDI-Driven Indoor Positioning and Assistance via Hermes Mesh Networks and LLM Interfaces", in Proc. 23rd IEEE Int. Conf. Pervasive Intelligence and Computing (PICom).
Bor, M., Roedig, U., Voigt, T. and Alonso, J. M. (2016) "Do LoRa Low-Power Wide-Area Networks Scale?", in Proc. 19th ACM Int. Conf. Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM), Malta, pp. 59–67.
Brown, T. B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P. et al. (2020) "Language Models are Few-Shot Learners", in Advances in Neural Information Processing Systems (NeurIPS), vol. 33, pp. 1877–1901.
Casals, L., Mir, B., Vidal, R. and Gomez, C. (2017) "Modeling the Energy Performance of LoRaWAN", Sensors, vol. 17, no. 10, p. 2364.
Cattani, M., Boano, C. A. and Römer, K. (2017) "An Experimental Evaluation of the Reliability of LoRa Long-Range Low-Power Wireless Communication", J. Sensor Actuator Networks, vol. 6, no. 2, p. 7.
Goldsmith, A. (2005) Wireless Communications, Cambridge University Press, Cambridge, UK.
Liando, J. C., Gamage, A., Tengourtius, A. W. and Li, M. (2019) "Known and Unknown Facts of LoRa: Experiences from a Large-Scale Measurement Study", ACM Trans. Sensor Networks, vol. 15, no. 2, pp. 1–35.
Liu, F. T., Ting, K. M. and Zhou, Z.-H. (2008) "Isolation Forest", in Proc. 8th IEEE Int. Conf. Data Mining (ICDM), Pisa, Italy, pp. 413–422.
Rappaport, T. S. (2002) Wireless Communications: Principles and Practice, 2nd ed., Prentice Hall, Upper Saddle River, NJ, USA.
Semtech Corporation (2020) "SX1276/77/78/79 Datasheet", Rev. 7. Available: [link].
Senol, N. S., Baza, M., Rasheed, A. and Alsabaan, M. (2024) "Privacy-Preserving Detection of Tampered Radio-Frequency Transmissions Utilizing Federated Learning in LoRa Networks", Sensors, vol. 24, no. 22, p. 7336.
Solé, J. M., Centelles, R. P., Freitag, F. and Meseguer, R. (2022) "Implementation of a LoRa Mesh Library", IEEE Access, vol. 10, pp. 113158–113171.
Solé, J. M., Freitag, F., Navarro, L. and Selimi, M. (2025) "Demonstration of Concurrent Application Provision with LoRaMesher", in Proc. 7th Experiment@ International Conference (exp.at'25), Faial, Azores, Portugal, pp. 231.
Winter, T., Thubert, P., Brandt, A., Hui, J., Kelsey, R., Levis, P., Pister, K., Struik, R., Vasseur, J. P. and Alexander, R. (2012) "RPL: IPv6 Routing Protocol for Low-Power and Lossy Networks", RFC 6550, IETF.
Xu, W., Ma, K., Trappe, W. and Zhang, Y. (2006) "Jamming Sensor Networks: Attack and Defense Strategies", IEEE Network, vol. 20, no. 3, pp. 41–47.
Xu, W., Trappe, W., Zhang, Y. and Wood, T. (2005) "The Feasibility of Launching and Detecting Jamming Attacks in Wireless Networks", in Proc. 6th ACM Int. Symp.
Mobile Ad Hoc Networking and Computing (MobiHoc), Urbana-Champaign, IL, USA, pp. 46–57.
Zhou, Y., Hsieh, K., Mani, S. K., Kandula, S. and Liu, Z. (2025) "MeshAgent: Enabling Reliable Network Management with Large Language Models", Proc. ACM Meas. Anal. Comput. Syst., vol. 9, no. 3, Art. 52.
Publicado
25/05/2026
Como Citar
FREITAS, Juliano Paulo de; VIEIRA, Flávio Henrique Teles.
Detecção de Anomalias e Falhas em Redes LoRa Mesh: Uma Abordagem com Isolation Forest e LLM para Redução de Falsos Positivos. In: WORKSHOP DE TESTES E TOLERÂNCIA A FALHAS (WTF), 27. , 2026, Praia do Forte/BA.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2026
.
p. 108-121.
ISSN 2595-2684.
DOI: https://doi.org/10.5753/wtf.2026.24133.
