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You're reading from  Hands-On Graph Neural Networks Using Python

Product typeBook
Published inApr 2023
PublisherPackt
ISBN-139781804617526
Edition1st Edition
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Neural Networks
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Maxime Labonne
Maxime Labonne
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Maxime Labonne

Maxime Labonne is currently a senior applied researcher at Airbus. He received a M.Sc. degree in computer science from INSA CVL, and a Ph.D. in machine learning and cyber security from the Polytechnic Institute of Paris. During his career, he worked on computer networks and the problem of representation learning, which led him to explore graph neural networks. He applied this knowledge to various industrial projects, including intrusion detection, satellite communications, quantum networks, and AI-powered aircrafts. He is now an active graph neural network evangelist through Twitter and his personal blog.
Read more about Maxime Labonne

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Exploring the CIDDS-001 dataset

This section will explore the dataset and get more insights about feature importance and scaling.

The CIDDS-001 dataset [1] is designed to train and evaluate anomaly-based network intrusion detection systems. It provides realistic traffic that includes up-to-date attacks to assess these systems. It was created by collecting and labeling 8,451,520 traffic flows in a virtual environment using OpenStack. Precisely, each row corresponds to a NetFlow connection, describing Internet Protocol (IP) traffic statistics, such as the number of bytes exchanged.

The following figure provides an overview of the simulated network environment in CIDDS-001.

Figure 16.1 – Overview of the virtual network simulated by CIDDS-001

Figure 16.1 – Overview of the virtual network simulated by CIDDS-001

We see four different subnets (developer, office, management, and server) with their respective IP address ranges. All these subnets are linked to a single server connected to the internet through a firewall...

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Hands-On Graph Neural Networks Using Python
Published in: Apr 2023Publisher: PacktISBN-13: 9781804617526
© 2023 Packt Publishing Limited All Rights Reserved

Author (1)

author image
Maxime Labonne

Maxime Labonne is currently a senior applied researcher at Airbus. He received a M.Sc. degree in computer science from INSA CVL, and a Ph.D. in machine learning and cyber security from the Polytechnic Institute of Paris. During his career, he worked on computer networks and the problem of representation learning, which led him to explore graph neural networks. He applied this knowledge to various industrial projects, including intrusion detection, satellite communications, quantum networks, and AI-powered aircrafts. He is now an active graph neural network evangelist through Twitter and his personal blog.
Read more about Maxime Labonne

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