AnubisFlow: a feature extractor for distributed denial of service attack classification (2021)
- Authors:
- USP affiliated authors: BATISTA, DANIEL MACEDO - IME ; HIRATA JUNIOR, ROBERTO - IME ; BARZILAY, ALAN - IME ; MARTINELLI, CAIO LORENZETTI - IME
- Unidade: IME
- DOI: 10.1109/NoF52522.2021.9609918
- Subjects: MODELOS ANALÍTICOS; CRIME POR COMPUTADOR
- Keywords: Distributed Denial of Service; Intrusion Detection System; Feature Extraction
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Publisher: IEEE
- Publisher place: Piscataway
- Date published: 2021
- Source:
- Título: Proceedings
- Conference titles: International Conference on Network of the Future - NoF
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
BARZILAY, Alan et al. AnubisFlow: a feature extractor for distributed denial of service attack classification. 2021, Anais.. Piscataway: IEEE, 2021. Disponível em: https://doi.org/10.1109/NoF52522.2021.9609918. Acesso em: 03 jan. 2026. -
APA
Barzilay, A., Martinelli, C. L., Nogueira, M., Batista, D. M., & Hirata Júnior, R. (2021). AnubisFlow: a feature extractor for distributed denial of service attack classification. In Proceedings. Piscataway: IEEE. doi:10.1109/NoF52522.2021.9609918 -
NLM
Barzilay A, Martinelli CL, Nogueira M, Batista DM, Hirata Júnior R. AnubisFlow: a feature extractor for distributed denial of service attack classification [Internet]. Proceedings. 2021 ;[citado 2026 jan. 03 ] Available from: https://doi.org/10.1109/NoF52522.2021.9609918 -
Vancouver
Barzilay A, Martinelli CL, Nogueira M, Batista DM, Hirata Júnior R. AnubisFlow: a feature extractor for distributed denial of service attack classification [Internet]. Proceedings. 2021 ;[citado 2026 jan. 03 ] Available from: https://doi.org/10.1109/NoF52522.2021.9609918 - Using natural language processing techniques for automated code refactoring
- Node concordance: a local homophily prediction task in graphs
- A crash response system using LoRa-based V2X communications
- An improved tool for detection of XSS attacks by combining CNN with LSTM
- A network intrusion detection system using deep learning against MQTT attacks in IoT
- Positive definite kernel functions on fuzzy sets
- Cross product kernels for fuzzy set similarity
- Optical mark recognition: advances, difculties, and imitations
- InterSCity: addressing future internet research challenges for smart cities
- A lean and modular two-stage network intrusion detection system for iot traffic
Informações sobre o DOI: 10.1109/NoF52522.2021.9609918 (Fonte: oaDOI API)
Download do texto completo
| Tipo | Nome | Link | |
|---|---|---|---|
 |
3062818.pdf |
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
