Research Areas
Biography and Research Information
OverviewAI-generated summary
Joseph P Dumond's research focuses on the application of machine learning techniques for network security, with a particular emphasis on intrusion recognition and anomaly detection in operational technology (OT) networks. He has investigated the use of autoencoders, including GRU-based models, for real-time anomaly detection and developed P4-based applications for smart grid security. His work also extends to exploring flow-level autoencoders for intrusion recognition systems. Dumond has contributed to the field through publications in recent years, indicating ongoing activity in his research area.
Metrics
- Publications: 1
Selected Publications
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FLAIR- Flow-Level Anomaly Intrustion Recognition (2026)Journal of the Arkansas Academy of Science OpenAlex
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Real-Time Anomaly Detection in OT Networks Using GRU-Based Autoencoders (2025)
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Developing P4-Based Applications on Academic Cloud Platforms for Smart Grid Security, Resilience, and Workforce Development (2025)
Collaboration Network
Top Collaborators
- Developing P4-Based Applications on Academic Cloud Platforms for Smart Grid Security, Resilience, and Workforce Development
- Real-Time Anomaly Detection in OT Networks Using GRU-Based Autoencoders
- Developing P4-Based Applications on Academic Cloud Platforms for Smart Grid Security, Resilience, and Workforce Development
- Developing P4-Based Applications on Academic Cloud Platforms for Smart Grid Security, Resilience, and Workforce Development
- Developing P4-Based Applications on Academic Cloud Platforms for Smart Grid Security, Resilience, and Workforce Development
- Developing P4-Based Applications on Academic Cloud Platforms for Smart Grid Security, Resilience, and Workforce Development
- Real-Time Anomaly Detection in OT Networks Using GRU-Based Autoencoders
- Real-Time Anomaly Detection in OT Networks Using GRU-Based Autoencoders
- Real-Time Anomaly Detection in OT Networks Using GRU-Based Autoencoders
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