Deployable Machine Learning for Security Defense
First International Workshop, MLHat 2020, San Diego, CA, USA, August 24, 2020, Proceedings
Published on 18. October 2020
Book
Paperback/Softback
VII, 165 pages
978-3-030-59620-0 (ISBN)
Description
This book constitutes selected papers from the First International Workshop on Deployable Machine Learning for Security Defense, MLHat 2020, held in August 2020. Due to the COVID-19 pandemic the conference was held online.
The 8 full papers were thoroughly reviewed and selected from 13 qualified submissions. The papers are organized in the following topical sections: understanding the adversaries; adversarial ML for better security; threats on networks.
The 8 full papers were thoroughly reviewed and selected from 13 qualified submissions. The papers are organized in the following topical sections: understanding the adversaries; adversarial ML for better security; threats on networks.
More details
Series
Edition
1st ed. 2020
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Illustrations
125 s/w Abbildungen, 45 farbige Abbildungen
VII, 165 p. 170 illus., 45 illus. in color.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 10 mm
Weight
277 gr
ISBN-13
978-3-030-59620-0 (9783030596200)
DOI
10.1007/978-3-030-59621-7
Schweitzer Classification
Other editions
Additional editions
Gang Wang | Arridhana Ciptadi | Ali Ahmadzadeh
Deployable Machine Learning for Security Defense
First International Workshop, MLHat 2020, San Diego, CA, USA, August 24, 2020, Proceedings
E-Book
10/2020
Springer
€80.24
Available for download
Content
Understanding the Adversaries.- Adversarial ML for Better Security.- Threats on Networks.