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Towards Representation Learning for Robust Network Intrusion Detection Systems
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posted on 2024-06-03, 18:55
authored by
Ryan John Hosler
Ryan John Hosler
<p dir="ltr">This research involves numerous network intrusion techniques through novel applications of graph representation learning and image representation learning. The methods are tested on multiple publicly available network flow datasets.</p>
History
Degree Type
Doctor of Philosophy
Department
Computer Science
Campus location
Indianapolis
Advisor/Supervisor/Committee Chair
Dr. Xukai Zou
Advisor/Supervisor/Committee co-chair
Dr. Feng Li
Additional Committee Member 2
Dr. Gavriil Tsechpenakis
Additional Committee Member 3
Dr. Arjan Durresi
Additional Committee Member 4
Dr. Qin Hu
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Categories
System and network security
Deep learning
Neural networks
Keywords
Graph Representation Model
image embedding
Network intrusion detection framework
Android malware analysis and detection
autoencoder neural networks
Wasserstein Generative Adversarial ...
bidirectional generative adversarial network
deep graph convolutional neural networks
network flow modelling
Licence
CC BY 4.0
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