Seminario 20/22: David Ríos (Real Academia de Ciencias), Adversarial Machine Learning: Perspectives from Adversarial Risk Analysis

Información

  • Ponente: David Ríos, Real Academia de Ciencias
  • Fecha: 03/nov/2020 - 12:00 horas
  • Lugar: Seminarios online CIO: meet.google.com/hnj-bdpz-rft
Machine_learning

Adversarial Machine Learning (AML) is emerging as a major field aimed at the protection of automated ML systems against security threats. The majority of work in this area has built upon a game-theoretic framework by modelling a conflict between an attacker and a defender. After reviewing game-theoretic approaches to AML, we discuss the benefits that adversarial risk analysis perspectives bring in when defending ML based systems and identify relevant research directions.

Deja un comentario

Tu dirección de correo no se publicará. Los campos obligatorios están marcados con *

Puedes usar las siguientes etiquetas y atributos HTML: <a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <strike> <strong>

borrarEnviar comentario