Deployable Machine Learning for Security Defense: First International Workshop, MLHat 2020, San Diego,...

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Gang Wang Arridhana Ciptadi

Deployable Machine Learning for Security Defense

Name: Deployable Machine Learning for Security Defense
Price: 153.86 AUD
Availability: OutOfStock
ISBN: 9783030596200

First International Workshop, MLHat 2020, San Diego, CA, USA, August 24, 2020, Proceedings

Gang Wang, Arridhana Ciptadi, Ali Ahmadzadeh

$191.95 $153.86

Paperback

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English

Springer Nature Switzerland AG
18 October 2020

Computing: general; Computer security; Computer fraud & hacking; Network security; Artificial intelligence

Series: Communications in Computer and Information Science

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.

Edited by: Gang Wang, Arridhana Ciptadi, Ali Ahmadzadeh
Imprint: Springer Nature Switzerland AG
Country of Publication: Switzerland
Edition: 1st ed. 2020
Volume: 1271
Dimensions: Height: 235mm, Width: 155mm,
Weight: 454g
ISBN: 9783030596200
ISBN 10: 3030596206
Series: Communications in Computer and Information Science
Pages: 165
Publication Date: 18 October 2020
Audience: Professional and scholarly , Undergraduate
Format: Paperback
Publisher's Status: Active

Understanding the Adversaries.- Adversarial ML for Better Security.- Threats on Networks.