David A. Bierbrauer

According to our database, David A. Bierbrauer authored at least 7 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Data-efficient Federated Learning for Edge Network Intrusion Detection.

David A. Bierbrauer, Sean M. Coffey, Mikal R. Willeke, John D. Beggs, Nathaniel D. Bastian

Eng. Appl. Artif. Intell., 2025

2024

ACI IoT Network Traffic Dataset 2023.

Nathaniel D. Bastian, David A. Bierbrauer, Morgan C. McKenzie, Emily A. Nack

Dataset, April, 2024

Offline Reinforcement Learning for Autonomous Cyber Defense Agents.

Alexander Wei, David A. Bierbrauer, Emily A. Nack, John A. Pavlik, Nathaniel D. Bastian

Proceedings of the Winter Simulation Conference, 2024

2023

Transfer learning for raw network traffic detection.

David A. Bierbrauer, Michael J. De Lucia, Krishna Reddy, Paul Maxwell, Nathaniel D. Bastian

Expert Syst. Appl., 2023

Uncertainty-Quantified, Robust Deep Learning for Network Intrusion Detection.

Joshua A. Wong, Alexander M. Berenbeim, David A. Bierbrauer, Nathaniel D. Bastian

Proceedings of the Winter Simulation Conference, 2023

2022

Payload-Byte: A Tool for Extracting and Labeling Packet Capture Files of Modern Network Intrusion Detection Datasets.

Yasir Ali Farrukh, Irfan Khan, Syed Wali, David A. Bierbrauer, John A. Pavlik, Nathaniel D. Bastian

Proceedings of the IEEE/ACM International Conference on Big Data Computing, 2022

2021

Anomaly Detection in Cybersecurity: Unsupervised, Graph-Based and Supervised Learning Methods in Adversarial Environments.

David A. Bierbrauer, Alexander Chang, Will Kritzer, Nathaniel D. Bastian

CoRR, 2021