Deployable Machine Learning for Security Defense
First International Workshop, MLHat 2020, San Diego, CA, USA, August 24, 2020, Proceedings
Published on 17. October 2020
VII, 165 pages
978-3-030-59621-7 (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
Product notice
Reflowable
Illustrations
VII, 165 p. 170 illus., 45 illus. in color.
ISBN-13
978-3-030-59621-7 (9783030596217)
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
Book
10/2020
Springer
€80.24
Shipment within 7-9 days
Content
Understanding the Adversaries.- Adversarial ML for Better Security.- Threats on Networks.
