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Trabalho de evento
On the use of machine learning for modern IoT ELF malware detection (2025)
Souza, Cristian H.M. ; Batista, Daniel Macêdo
Source: Proceedings. Conference titles: IEEE Latin American Conference on Computational Intelligence - LA-CCI. Unidade: IME
Subjects: APRENDIZADO COMPUTACIONAL, GESTÃO DA SEGURANÇA EM SISTEMAS COMPUTACIONAIS
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ABNT
SOUZA, Cristian H.M. e BATISTA, Daniel Macêdo. On the use of machine learning for modern IoT ELF malware detection. 2025, Anais.. Piscataway: IEEE, 2025. p. 1-6. Disponível em: https://repositorio.usp.br/directbitstream/2b6f0605-3ca7-42af-ac9b-a9a8f1e8f68d/3272162_va.pdf. Acesso em: 08 out. 2025.
APA
Souza, C. H. M., & Batista, D. M. (2025). On the use of machine learning for modern IoT ELF malware detection. In Proceedings (p. 1-6). Piscataway: IEEE. Recuperado de https://repositorio.usp.br/directbitstream/2b6f0605-3ca7-42af-ac9b-a9a8f1e8f68d/3272162_va.pdf
NLM
Souza CHM, Batista DM. On the use of machine learning for modern IoT ELF malware detection [Internet]. Proceedings. 2025 ; 1-6.[citado 2025 out. 08 ] Available from: https://repositorio.usp.br/directbitstream/2b6f0605-3ca7-42af-ac9b-a9a8f1e8f68d/3272162_va.pdf
Vancouver
Souza CHM, Batista DM. On the use of machine learning for modern IoT ELF malware detection [Internet]. Proceedings. 2025 ; 1-6.[citado 2025 out. 08 ] Available from: https://repositorio.usp.br/directbitstream/2b6f0605-3ca7-42af-ac9b-a9a8f1e8f68d/3272162_va.pdf
Trabalho de evento
An RNN approach to real-time multimedia QoE assessment via facial expressions (2024)
Pereira Neto, Eduardo Lopes; Hayashi, Sergio; Batista, Daniel Macêdo ; Hirata Júnior, Roberto ; Hirata, Nina Sumiko Tomita ; Delgado, Karina Valdivia
Source: Proceedings. Conference titles: Virtual Conference on Communications - VCC. Unidades: EACH, IME
Subjects: TEMPO-REAL, PLATAFORMA DIGITAL, COMUNICAÇÃO DIGITAL, EXPRESSÃO FACIAL
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ABNT
PEREIRA NETO, Eduardo Lopes et al. An RNN approach to real-time multimedia QoE assessment via facial expressions. 2024, Anais.. Piscataway: IEEE, 2024. Disponível em: https://doi.org/10.1109/VCC63113.2024.10914430. Acesso em: 08 out. 2025.
APA
Pereira Neto, E. L., Hayashi, S., Batista, D. M., Hirata Júnior, R., Hirata, N. S. T., & Delgado, K. V. (2024). An RNN approach to real-time multimedia QoE assessment via facial expressions. In Proceedings. Piscataway: IEEE. doi:10.1109/VCC63113.2024.10914430
NLM
Pereira Neto EL, Hayashi S, Batista DM, Hirata Júnior R, Hirata NST, Delgado KV. An RNN approach to real-time multimedia QoE assessment via facial expressions [Internet]. Proceedings. 2024 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/VCC63113.2024.10914430
Vancouver
Pereira Neto EL, Hayashi S, Batista DM, Hirata Júnior R, Hirata NST, Delgado KV. An RNN approach to real-time multimedia QoE assessment via facial expressions [Internet]. Proceedings. 2024 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/VCC63113.2024.10914430
Trabalho de evento
Real-time intrusion detection with sequence-aware neural networks for Internet of medical things (2024)
Werneck, Heitor; Batista, Daniel Macêdo ; Hirata Júnior, Roberto ; Queiroz, Marcelo Gomes de
Source: Proceedings. Conference titles: Virtual Conference on Communications - VCC. Unidade: IME
Subjects: APRENDIZADO COMPUTACIONAL, INTERNET DAS COISAS, SAÚDE, REDES NEURAIS, GESTÃO DA SEGURANÇA EM SISTEMAS COMPUTACIONAIS
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ABNT
WERNECK, Heitor et al. Real-time intrusion detection with sequence-aware neural networks for Internet of medical things. 2024, Anais.. Piscataway: IEEE, 2024. Disponível em: https://doi.org/10.1109/VCC63113.2024.10914399. Acesso em: 08 out. 2025.
APA
Werneck, H., Batista, D. M., Hirata Júnior, R., & Queiroz, M. G. de. (2024). Real-time intrusion detection with sequence-aware neural networks for Internet of medical things. In Proceedings. Piscataway: IEEE. doi:10.1109/VCC63113.2024.10914399
NLM
Werneck H, Batista DM, Hirata Júnior R, Queiroz MG de. Real-time intrusion detection with sequence-aware neural networks for Internet of medical things [Internet]. Proceedings. 2024 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/VCC63113.2024.10914399
Vancouver
Werneck H, Batista DM, Hirata Júnior R, Queiroz MG de. Real-time intrusion detection with sequence-aware neural networks for Internet of medical things [Internet]. Proceedings. 2024 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/VCC63113.2024.10914399
Trabalho de evento
Unsupervised AutoML and dimensionality reduction for autonomous DDoS attack prediction (2024)
Neira, Anderson B.; Borges, Ligia F.; Batista, Daniel Macêdo ; Nogueira, Michele
Source: Proceedings. Conference titles: IEEE Latin-American Conference on Communications - LATINCOM. Unidade: IME
Subjects: APRENDIZADO COMPUTACIONAL, CRIME POR COMPUTADOR, SEGURANÇA DE REDES
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ABNT
NEIRA, Anderson B. et al. Unsupervised AutoML and dimensionality reduction for autonomous DDoS attack prediction. 2024, Anais.. Piscataway: IEEE, 2024. Disponível em: https://doi.org/10.1109/LATINCOM62985.2024.10770668. Acesso em: 08 out. 2025.
APA
Neira, A. B., Borges, L. F., Batista, D. M., & Nogueira, M. (2024). Unsupervised AutoML and dimensionality reduction for autonomous DDoS attack prediction. In Proceedings. Piscataway: IEEE. doi:10.1109/LATINCOM62985.2024.10770668
NLM
Neira AB, Borges LF, Batista DM, Nogueira M. Unsupervised AutoML and dimensionality reduction for autonomous DDoS attack prediction [Internet]. Proceedings. 2024 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/LATINCOM62985.2024.10770668
Vancouver
Neira AB, Borges LF, Batista DM, Nogueira M. Unsupervised AutoML and dimensionality reduction for autonomous DDoS attack prediction [Internet]. Proceedings. 2024 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/LATINCOM62985.2024.10770668
Trabalho de evento
A lean and modular two-stage network intrusion detection system for iot traffic (2024)
Inácio, Bruno Brandão; Araújo, Juliana C. Carvalho de; Dos Santos, Aldri L.; Nogueira, Michele ; Hirata Júnior, Roberto ; Batista, Daniel Macêdo
Source: Proceedings. Conference titles: Latin-American Conference on Communications - LATINCOM. Unidade: IME
Subjects: GESTÃO DA SEGURANÇA EM SISTEMAS COMPUTACIONAIS, CRIME POR COMPUTADOR, INTERNET DAS COISAS
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ABNT
INÁCIO, Bruno Brandão et al. A lean and modular two-stage network intrusion detection system for iot traffic. 2024, Anais.. Piscataway: IEEE, 2024. Disponível em: https://doi.org/10.1109/LATINCOM62985.2024.10770670. Acesso em: 08 out. 2025.
APA
Inácio, B. B., Araújo, J. C. C. de, Dos Santos, A. L., Nogueira, M., Hirata Júnior, R., & Batista, D. M. (2024). A lean and modular two-stage network intrusion detection system for iot traffic. In Proceedings. Piscataway: IEEE. doi:10.1109/LATINCOM62985.2024.10770670
NLM
Inácio BB, Araújo JCC de, Dos Santos AL, Nogueira M, Hirata Júnior R, Batista DM. A lean and modular two-stage network intrusion detection system for iot traffic [Internet]. Proceedings. 2024 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/LATINCOM62985.2024.10770670
Vancouver
Inácio BB, Araújo JCC de, Dos Santos AL, Nogueira M, Hirata Júnior R, Batista DM. A lean and modular two-stage network intrusion detection system for iot traffic [Internet]. Proceedings. 2024 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/LATINCOM62985.2024.10770670
Trabalho de evento
Towards a transformer-based pre-trained model for IoT traffic classification (2024)
Bazaluk, Bruna ; Hamdan, Mosab ; Ghaleb, Mustafa ; Gismalla, Mohammed Salih Mohammed ; Silva, Flávio Soares Corrêa da ; Batista, Daniel Macêdo
Source: Proceedings. Conference titles: Network Operations and Management Symposium - NOMS. Unidade: IME
Subjects: INTERNET DAS COISAS, APRENDIZADO COMPUTACIONAL, APRENDIZAGEM PROFUNDA
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ABNT
BAZALUK, Bruna et al. Towards a transformer-based pre-trained model for IoT traffic classification. 2024, Anais.. Piscataway: IEEE, 2024. Disponível em: https://doi.org/10.1109/NOMS59830.2024.10575448. Acesso em: 08 out. 2025.
APA
Bazaluk, B., Hamdan, M., Ghaleb, M., Gismalla, M. S. M., Silva, F. S. C. da, & Batista, D. M. (2024). Towards a transformer-based pre-trained model for IoT traffic classification. In Proceedings. Piscataway: IEEE. doi:10.1109/NOMS59830.2024.10575448
NLM
Bazaluk B, Hamdan M, Ghaleb M, Gismalla MSM, Silva FSC da, Batista DM. Towards a transformer-based pre-trained model for IoT traffic classification [Internet]. Proceedings. 2024 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/NOMS59830.2024.10575448
Vancouver
Bazaluk B, Hamdan M, Ghaleb M, Gismalla MSM, Silva FSC da, Batista DM. Towards a transformer-based pre-trained model for IoT traffic classification [Internet]. Proceedings. 2024 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/NOMS59830.2024.10575448
Trabalho de evento
A two-tier anomaly-based intrusion detection approach for IoT-enabled smart cities (2023)
Hamdan, Mosab ; Eldhai, Arwa M; Abdelsalam, Samah; Ullah, Kifayat ; Bashir, Ali Kashif ; Marsono, MN ; Kon, Fábio ; Batista, Daniel Macêdo
Source: Proceedings. Conference titles: Conference on Computer Communications Workshops -INFOCOM WKSHPS. Unidade: IME
Subjects: INTERNET DAS COISAS, APRENDIZADO COMPUTACIONAL
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ABNT
HAMDAN, Mosab et al. A two-tier anomaly-based intrusion detection approach for IoT-enabled smart cities. 2023, Anais.. Piscataway: IEEE, 2023. Disponível em: https://doi.org/10.1109/INFOCOMWKSHPS57453.2023.10225834. Acesso em: 08 out. 2025.
APA
Hamdan, M., Eldhai, A. M., Abdelsalam, S., Ullah, K., Bashir, A. K., Marsono, M. N., et al. (2023). A two-tier anomaly-based intrusion detection approach for IoT-enabled smart cities. In Proceedings. Piscataway: IEEE. doi:10.1109/INFOCOMWKSHPS57453.2023.10225834
NLM
Hamdan M, Eldhai AM, Abdelsalam S, Ullah K, Bashir AK, Marsono MN, Kon F, Batista DM. A two-tier anomaly-based intrusion detection approach for IoT-enabled smart cities [Internet]. Proceedings. 2023 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/INFOCOMWKSHPS57453.2023.10225834
Vancouver
Hamdan M, Eldhai AM, Abdelsalam S, Ullah K, Bashir AK, Marsono MN, Kon F, Batista DM. A two-tier anomaly-based intrusion detection approach for IoT-enabled smart cities [Internet]. Proceedings. 2023 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/INFOCOMWKSHPS57453.2023.10225834
Trabalho de evento
Intrusion detection system for IoHT devices using federated learning (2023)
Mosaiyebzadeh, Fatemeh; Pouriyeh, Seyedamin ; Parizi, Reza M ; Han, Meng ; Batista, Daniel Macêdo
Source: Proceedings. Conference titles: Conference on Computer Communications Workshops -INFOCOM WKSHPS. Unidade: IME
Subjects: INTERNET DAS COISAS, APRENDIZAGEM PROFUNDA, AVALIAÇÃO DE DESEMPENHO
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ABNT
MOSAIYEBZADEH, Fatemeh et al. Intrusion detection system for IoHT devices using federated learning. 2023, Anais.. Piscataway: IEEE, 2023. Disponível em: https://doi.org/10.1109/INFOCOMWKSHPS57453.2023.10225932. Acesso em: 08 out. 2025.
APA
Mosaiyebzadeh, F., Pouriyeh, S., Parizi, R. M., Han, M., & Batista, D. M. (2023). Intrusion detection system for IoHT devices using federated learning. In Proceedings. Piscataway: IEEE. doi:10.1109/INFOCOMWKSHPS57453.2023.10225932
NLM
Mosaiyebzadeh F, Pouriyeh S, Parizi RM, Han M, Batista DM. Intrusion detection system for IoHT devices using federated learning [Internet]. Proceedings. 2023 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/INFOCOMWKSHPS57453.2023.10225932
Vancouver
Mosaiyebzadeh F, Pouriyeh S, Parizi RM, Han M, Batista DM. Intrusion detection system for IoHT devices using federated learning [Internet]. Proceedings. 2023 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/INFOCOMWKSHPS57453.2023.10225932
Trabalho de evento
Applying Hoeffding tree algorithms for effective stream learning in IoT DDoS detection (2023)
Josephik, João Gabriel Andrade de Araújo ; Siqueira, Yaissa; Machado, Kétly Gonçalves ; Terada, Routo ; Santos, Aldri Luiz Dos ; Nogueira, Michele ; Batista, Daniel Macêdo
Source: Proceedings. Conference titles: Latin-American Conference on Communications - LATINCOM. Unidade: IME
Subjects: INTERNET DAS COISAS, CRIME POR COMPUTADOR, SOFTWARE LIVRE
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ABNT
JOSEPHIK, João Gabriel Andrade de Araújo et al. Applying Hoeffding tree algorithms for effective stream learning in IoT DDoS detection. 2023, Anais.. Piscataway: IEEE, 2023. Disponível em: https://doi.org/10.1109/LATINCOM59467.2023.10361862. Acesso em: 08 out. 2025.
APA
Josephik, J. G. A. de A., Siqueira, Y., Machado, K. G., Terada, R., Santos, A. L. D., Nogueira, M., & Batista, D. M. (2023). Applying Hoeffding tree algorithms for effective stream learning in IoT DDoS detection. In Proceedings. Piscataway: IEEE. doi:10.1109/LATINCOM59467.2023.10361862
NLM
Josephik JGA de A, Siqueira Y, Machado KG, Terada R, Santos ALD, Nogueira M, Batista DM. Applying Hoeffding tree algorithms for effective stream learning in IoT DDoS detection [Internet]. Proceedings. 2023 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/LATINCOM59467.2023.10361862
Vancouver
Josephik JGA de A, Siqueira Y, Machado KG, Terada R, Santos ALD, Nogueira M, Batista DM. Applying Hoeffding tree algorithms for effective stream learning in IoT DDoS detection [Internet]. Proceedings. 2023 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/LATINCOM59467.2023.10361862
Trabalho de evento
A pothole warning system using vehicular ad-hoc networks (VANETs) (2022)
Nepomuceno, Pedro Ivo Siqueira; Ullah, Kifayat; Braghetto, Kelly Rosa ; Batista, Daniel Macêdo
Source: Proceedings. Conference titles: International Conference on Frontiers of Information Technology - FIT. Unidade: IME
Subjects: REDES AD HOC VEICULARES, SISTEMAS INTELIGENTES DE TRANSPORTES, VEÍCULOS AUTÔNOMOS, INTELIGÊNCIA ARTIFICIAL
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ABNT
NEPOMUCENO, Pedro Ivo Siqueira et al. A pothole warning system using vehicular ad-hoc networks (VANETs). 2022, Anais.. Piscataway: IEEE, 2022. Disponível em: https://doi.org/10.1109/FIT57066.2022.00036. Acesso em: 08 out. 2025.
APA
Nepomuceno, P. I. S., Ullah, K., Braghetto, K. R., & Batista, D. M. (2022). A pothole warning system using vehicular ad-hoc networks (VANETs). In Proceedings. Piscataway: IEEE. doi:10.1109/FIT57066.2022.00036
NLM
Nepomuceno PIS, Ullah K, Braghetto KR, Batista DM. A pothole warning system using vehicular ad-hoc networks (VANETs) [Internet]. Proceedings. 2022 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/FIT57066.2022.00036
Vancouver
Nepomuceno PIS, Ullah K, Braghetto KR, Batista DM. A pothole warning system using vehicular ad-hoc networks (VANETs) [Internet]. Proceedings. 2022 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/FIT57066.2022.00036
Trabalho de evento
A stacked ensemble classifier for an intrusion detection system in the edge of IoT and IIoT networks (2022)
Oliveira, Giovanni Aparecido da Silva ; Lima, Priscila Serra Silva; Kon, Fábio ; Terada, Routo ; Batista, Daniel Macêdo ; Hirata Júnior, Roberto ; Hamdan, Mosab
Source: Proceedings. Conference titles: Latin-American Conference on Communications - LATINCOM. Unidade: IME
Subjects: APRENDIZADO COMPUTACIONAL, INTERNET DAS COISAS
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ABNT
OLIVEIRA, Giovanni Aparecido da Silva et al. A stacked ensemble classifier for an intrusion detection system in the edge of IoT and IIoT networks. 2022, Anais.. Piscataway: IEEE, 2022. Disponível em: https://doi.org/10.1109/LATINCOM56090.2022.10000559. Acesso em: 08 out. 2025.
APA
Oliveira, G. A. da S., Lima, P. S. S., Kon, F., Terada, R., Batista, D. M., Hirata Júnior, R., & Hamdan, M. (2022). A stacked ensemble classifier for an intrusion detection system in the edge of IoT and IIoT networks. In Proceedings. Piscataway: IEEE. doi:10.1109/LATINCOM56090.2022.10000559
NLM
Oliveira GA da S, Lima PSS, Kon F, Terada R, Batista DM, Hirata Júnior R, Hamdan M. A stacked ensemble classifier for an intrusion detection system in the edge of IoT and IIoT networks [Internet]. Proceedings. 2022 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/LATINCOM56090.2022.10000559
Vancouver
Oliveira GA da S, Lima PSS, Kon F, Terada R, Batista DM, Hirata Júnior R, Hamdan M. A stacked ensemble classifier for an intrusion detection system in the edge of IoT and IIoT networks [Internet]. Proceedings. 2022 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/LATINCOM56090.2022.10000559
Trabalho de evento
A hybrid CNN-LSTM model for IIoT edge privacy-aware intrusion detection (2022)
Elias, Erik Miguel de ; Carriel, Vinicius Sanches; Oliveira, Guilherme Werneck de ; Santos, Aldri Luiz Dos ; Nogueira, Michele ; Hirata Júnior, Roberto ; Batista, Daniel Macêdo
Source: Proceedings. Conference titles: Latin-American Conference on Communications - LATINCOM. Unidade: IME
Assunto: APRENDIZADO COMPUTACIONAL
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ABNT
ELIAS, Erik Miguel de et al. A hybrid CNN-LSTM model for IIoT edge privacy-aware intrusion detection. 2022, Anais.. Piscataway: IEEE, 2022. Disponível em: https://doi.org/10.1109/LATINCOM56090.2022.10000468. Acesso em: 08 out. 2025.
APA
Elias, E. M. de, Carriel, V. S., Oliveira, G. W. de, Santos, A. L. D., Nogueira, M., Hirata Júnior, R., & Batista, D. M. (2022). A hybrid CNN-LSTM model for IIoT edge privacy-aware intrusion detection. In Proceedings. Piscataway: IEEE. doi:10.1109/LATINCOM56090.2022.10000468
NLM
Elias EM de, Carriel VS, Oliveira GW de, Santos ALD, Nogueira M, Hirata Júnior R, Batista DM. A hybrid CNN-LSTM model for IIoT edge privacy-aware intrusion detection [Internet]. Proceedings. 2022 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/LATINCOM56090.2022.10000468
Vancouver
Elias EM de, Carriel VS, Oliveira GW de, Santos ALD, Nogueira M, Hirata Júnior R, Batista DM. A hybrid CNN-LSTM model for IIoT edge privacy-aware intrusion detection [Internet]. Proceedings. 2022 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/LATINCOM56090.2022.10000468
Trabalho de evento
A network intrusion detection system using deep learning against MQTT attacks in IoT (2021)
Mosaiyebzadeh, Fatemeh ; Rodriguez, Luis Gustavo Araujo; Batista, Daniel Macêdo ; Hirata Júnior, Roberto
Source: Proceedings. Conference titles: Latin-American Conference on Communications - LATINCOM. Unidade: IME
Subjects: APRENDIZAGEM PROFUNDA, CIDADES INTELIGENTES, INTERNET DAS COISAS
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ABNT
MOSAIYEBZADEH, Fatemeh et al. A network intrusion detection system using deep learning against MQTT attacks in IoT. 2021, Anais.. Piscataway: IEEE, 2021. Disponível em: https://doi.org/10.1109/LATINCOM53176.2021.9647850. Acesso em: 08 out. 2025.
APA
Mosaiyebzadeh, F., Rodriguez, L. G. A., Batista, D. M., & Hirata Júnior, R. (2021). A network intrusion detection system using deep learning against MQTT attacks in IoT. In Proceedings. Piscataway: IEEE. doi:10.1109/LATINCOM53176.2021.9647850
NLM
Mosaiyebzadeh F, Rodriguez LGA, Batista DM, Hirata Júnior R. A network intrusion detection system using deep learning against MQTT attacks in IoT [Internet]. Proceedings. 2021 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/LATINCOM53176.2021.9647850
Vancouver
Mosaiyebzadeh F, Rodriguez LGA, Batista DM, Hirata Júnior R. A network intrusion detection system using deep learning against MQTT attacks in IoT [Internet]. Proceedings. 2021 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/LATINCOM53176.2021.9647850
Trabalho de evento
BGP anomalies classification using features based on AS relationship graphs (2021)
Paiva, Thales Bandiera ; Siqueira, Yaissa; Batista, Daniel Macêdo ; Hirata Júnior, Roberto ; Terada, Routo
Source: Proceedings. Conference titles: Latin-American Conference on Communications - LATINCOM. Unidade: IME
Subjects: APRENDIZADO COMPUTACIONAL, PROTOCOLOS DE COMUNICAÇÃO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
PAIVA, Thales Bandiera et al. BGP anomalies classification using features based on AS relationship graphs. 2021, Anais.. Piscataway: IEEE, 2021. Disponível em: https://doi.org/10.1109/LATINCOM53176.2021.9647824. Acesso em: 08 out. 2025.
APA
Paiva, T. B., Siqueira, Y., Batista, D. M., Hirata Júnior, R., & Terada, R. (2021). BGP anomalies classification using features based on AS relationship graphs. In Proceedings. Piscataway: IEEE. doi:10.1109/LATINCOM53176.2021.9647824
NLM
Paiva TB, Siqueira Y, Batista DM, Hirata Júnior R, Terada R. BGP anomalies classification using features based on AS relationship graphs [Internet]. Proceedings. 2021 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/LATINCOM53176.2021.9647824
Vancouver
Paiva TB, Siqueira Y, Batista DM, Hirata Júnior R, Terada R. BGP anomalies classification using features based on AS relationship graphs [Internet]. Proceedings. 2021 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/LATINCOM53176.2021.9647824
Trabalho de evento
Towards improving fuzzer efficiency for the MQTT protocol (2021)
Rodriguez, Luis Gustavo Araujo; Batista, Daniel Macêdo
Source: Proceedings. Conference titles: Symposium on Computers and Communications - ISCC. Unidade: IME
Subjects: ENGENHARIA DE CONHECIMENTO, INTERNET DAS COISAS, FUZZY (INTELIGÊNCIA ARTIFICIAL), TESTE E AVALIAÇÃO DE SOFTWARE
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ABNT
RODRIGUEZ, Luis Gustavo Araujo e BATISTA, Daniel Macêdo. Towards improving fuzzer efficiency for the MQTT protocol. 2021, Anais.. Piscataway: IEEE, 2021. Disponível em: https://doi.org/10.1109/ISCC53001.2021.9631520. Acesso em: 08 out. 2025.
APA
Rodriguez, L. G. A., & Batista, D. M. (2021). Towards improving fuzzer efficiency for the MQTT protocol. In Proceedings. Piscataway: IEEE. doi:10.1109/ISCC53001.2021.9631520
NLM
Rodriguez LGA, Batista DM. Towards improving fuzzer efficiency for the MQTT protocol [Internet]. Proceedings. 2021 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/ISCC53001.2021.9631520
Vancouver
Rodriguez LGA, Batista DM. Towards improving fuzzer efficiency for the MQTT protocol [Internet]. Proceedings. 2021 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/ISCC53001.2021.9631520
Trabalho de evento
Predicting response time in SDN-Fog environments for IIoT applications (2021)
Oliveira, Guilherme Werneck de ; Ney, Rodrigo Toscano; Herrera, Juan Luis ; Batista, Daniel Macêdo ; Hirata Júnior, Roberto ; Galán-Jiménez, Jaime ; Berrocal, Javier ; Murillo, Juan Manuel; Santos, Aldri Luiz Dos ; Nogueira, Michele
Source: Proceedings. Conference titles: Latin-American Conference on Communications - LATINCOM. Unidade: IME
Subjects: APRENDIZADO COMPUTACIONAL, INTERNET DAS COISAS, REGRESSÃO LINEAR
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ABNT
OLIVEIRA, Guilherme Werneck de et al. Predicting response time in SDN-Fog environments for IIoT applications. 2021, Anais.. Piscataway: IEEE, 2021. Disponível em: https://doi.org/10.1109/LATINCOM53176.2021.9647803. Acesso em: 08 out. 2025.
APA
Oliveira, G. W. de, Ney, R. T., Herrera, J. L., Batista, D. M., Hirata Júnior, R., Galán-Jiménez, J., et al. (2021). Predicting response time in SDN-Fog environments for IIoT applications. In Proceedings. Piscataway: IEEE. doi:10.1109/LATINCOM53176.2021.9647803
NLM
Oliveira GW de, Ney RT, Herrera JL, Batista DM, Hirata Júnior R, Galán-Jiménez J, Berrocal J, Murillo JM, Santos ALD, Nogueira M. Predicting response time in SDN-Fog environments for IIoT applications [Internet]. Proceedings. 2021 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/LATINCOM53176.2021.9647803
Vancouver
Oliveira GW de, Ney RT, Herrera JL, Batista DM, Hirata Júnior R, Galán-Jiménez J, Berrocal J, Murillo JM, Santos ALD, Nogueira M. Predicting response time in SDN-Fog environments for IIoT applications [Internet]. Proceedings. 2021 ;[citado 2025 out. 08 ] Available from: https://doi.org/10.1109/LATINCOM53176.2021.9647803

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