Deployable Machine Learning for Security Defense

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.

Contenu

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