Deployable Machine Learning for Security Defense: First International Workshop, MLHat 2020, San Diego, USA, August 24, Proceedings (Communications in Computer and Information Science (1271))

ISBN 10: 3030596206 / ISBN 13: 9783030596200

Published by Springer, 2020

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Bibliographic Details

• Title: Deployable Machine Learning for Security Defense: First International Workshop, MLHat 2020, San Diego, USA, August 24, Proceedings (Communications in Computer and Information Science (1271))
• Publisher: Springer
• Publication Date: 2020
• Language: English
• ISBN 10: 3030596206
• ISBN 13: 9783030596200
• Binding: Soft cover
• Condition: New

About this title

Synopsis

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.