|
Título:
|
Perspectives on Adversarial Classification
|
|
Autores:
|
Rios Insua, David ;
Naveiro, Roi ;
Gallego, Víctor
|
|
Tipo de documento:
|
texto impreso
|
|
Editorial:
|
MDPI, 2020-11-05
|
|
Dimensiones:
|
application/pdf
|
|
Nota general:
|
cc_by
info:eu-repo/semantics/openAccess
|
|
Idiomas:
|
|
|
Palabras clave:
|
Estado = Publicado
,
Materia = Ciencias: Informática
,
Materia = Ciencias: Informática: Seguridad informática
,
Materia = Ciencias: Matemáticas
,
Tipo = Artículo
|
|
Resumen:
|
Adversarial classification (AC) is a major subfield within the increasingly important domain of adversarial machine learning (AML). So far, most approaches to AC have followed a classical game-theoretic framework. This requires unrealistic common knowledge conditions untenable in the security settings typical of the AML realm. After reviewing such approaches, we present alternative perspectives on AC based on adversarial risk analysis.
|
|
En línea:
|
https://eprints.ucm.es/id/eprint/63167/1/rios-naveiro-gallego.pdf
|
