Deployable Machine Learning for Security Defense

"Deployable Machine Learning for Security Defense" is a collection of selected works presented at the first International Workshop on this topic, MLHat 2020. The workshop took place online in August 2020 due to the COVID-19 pandemic. This publication includes eight thoroughly peer-reviewed contributions selected from a total of 13 qualified submissions. The contributions are organized into various thematic sections that address threat analysis, the application of adversarial machine learning to enhance security, and challenges in the field of network security. This literature provides valuable insights into current developments and challenges in machine learning technologies for security applications and is aimed at professionals and researchers engaged with the intersection of technology and security.