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Deployable Machine Learning for Security Defense First International Workshop, MLHat 2020, San Diego, CA, USA, August 24, 2020, Proceedings / [electronic resource] : edited by Gang Wang, Arridhana Ciptadi, Ali Ahmadzadeh. - 1st ed. 2020. - VII, 165 p. 170 illus., 45 illus. in color. online resource. - Communications in Computer and Information Science, 1271 1865-0937 ; . - Communications in Computer and Information Science, 1271 .

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

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.

ISBN: 9783030596217

Standard No.: 10.1007/978-3-030-59621-7 doi

Subjects--Topical Terms:
Computers.
Data protection.
Computer crimes.
Artificial intelligence.
Computer networks .
Application software.
Computing Milieux.
Data and Information Security.
Computer Crime.
Artificial Intelligence.
Computer Communication Networks.
Computer and Information Systems Applications.

LC Class. No.: QA75.5-76.95

Dewey Class. No.: 004