Perspectives on Adversarial Classification
Perspectives on Adversarial Classification
D. Rios Insua,R. Naveiro,Víctor Gallego
TLDR
Alternative perspectives on AC based on adversarial risk analysis are presented, including a classical game-theoretic framework, which requires unrealistic common knowledge conditions untenable in the security settings typical of the AML realm.
Abstract
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.
