Towards Representation Learning for Robust Network Intrusion Detection Systems

Description

<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>

Links & Downloads

1. 10.25394/pgs.25607649.v1

Tags

System and network security

Deep learning

Neural networks

Graph Representation Model

image embedding

Network intrusion detection framework

Android malware analysis and detection

autoencoder neural networks

Wasserstein Generative Adversarial ...

deep graph convolutional neural networks

network flow modelling

Additional Fields

Identifer	oai:union.ndltd.org:purdue.edu/oai:figshare.com:article/25607649
Date	03 June 2024
Creators	Ryan John Hosler (18369510)
Source Sets	Purdue University
Detected Language	English
Type	Text, Thesis
Rights	CC BY 4.0
Relation	https://figshare.com/articles/thesis/Towards_Representation_Learning_for_Robust_Network_Intrusion_Detection_Systems/25607649