Binding: Paperback
Description: More frequent and complex cyber threats require robust automated and rapid responses from cyber - security specialists. This book offers a complete study in the area of graph learning in cyber emphasizing graph neural networks (GN Ns) and their cyber - security applications. Three parts examine the basics methods and practices and advanced topics. The first part presents a grounding in graph data structures and graph embedding and gives a taxonomic view of GN Ns and cyber - security applications. The second part explains three different categories of graph learning including deterministic generative and reinforcement learning and how they can be used for developing cyber defense models. The discussion of each category covers the applicability of simple and complex graphs scalability representative algorithms and technical details. Undergraduate students graduate students researchers cyber analysts and AI engineers looking to understand practical deep learning methods will find this book an invaluable resource.
Title: Responsible Graph Neural Networks
Author(s): Tari Zahir
Publisher: Taylor & Francis Ltd
Barcode: 9781032359885
Pages: 307 Pages, 41 Halftones, Black And White; 41 Illustrations, Black And White
Publication Date: 6/5/2023
Category: Neural Networks & Fuzzy Systems