2026-06-26T16:40:31Zhttps://docta.ucm.es/rest/oai/request

oai:docta.ucm.es:20.500.14352/75392023-07-18T23:32:12Zcom_20.500.14352_14col_20.500.14352_15

Rios Insua, David Naveiro, Roi Gallego, Víctor 2023-06-17T08:55:52Z 2023-06-17T08:55:52Z 2020-11-05 2227-7390 10.3390/math8111957 https://hdl.handle.net/20.500.14352/7539 https://doi.org/10.3390/math8111957 https://www.mdpi.com/2227-7390/8/11/1957 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. eng https://creativecommons.org/licenses/by/3.0/es/ open access Atribución 3.0 España Perspectives on Adversarial Classification journal article