Intrusion detection system for IoHT devices using federated learning (2023)
- Authors:
- USP affiliated authors: BATISTA, DANIEL MACEDO - IME ; MOSAIYEBZADEH, FATEMEH - IME
- Unidade: IME
- DOI: 10.1109/INFOCOMWKSHPS57453.2023.10225932
- Subjects: INTERNET DAS COISAS; APRENDIZAGEM PROFUNDA; AVALIAÇÃO DE DESEMPENHO
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Publisher: IEEE
- Publisher place: Piscataway
- Date published: 2023
- Source:
- Título: Proceedings
- Conference titles: Conference on Computer Communications Workshops -INFOCOM WKSHPS
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
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: 13 fev. 2026. -
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 2026 fev. 13 ] 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 2026 fev. 13 ] Available from: https://doi.org/10.1109/INFOCOMWKSHPS57453.2023.10225932 - Advances in application of federated machine learning for oncology and cancer diagnosis
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- Scheduling cloud applications under uncertain available bandwidth
Informações sobre o DOI: 10.1109/INFOCOMWKSHPS57453.2023.10225932 (Fonte: oaDOI API)
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