Perspectives on Adversarial Classification

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 settin...

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Detalles Bibliográficos
Autores: Rios Insua, David, Naveiro, Roi, Gallego, Víctor
Tipo de recurso: artículo
Fecha de publicación:2020
País:España
Institución:Universidad Complutense de Madrid (UCM)
Repositorio:Docta Complutense
Idioma:inglés
OAI Identifier:oai:docta.ucm.es:20.500.14352/7539
Acceso en línea:https://hdl.handle.net/20.500.14352/7539
Access Level:acceso abierto
Palabra clave:004.056
004.492
Classification
adversarial machine learning
security
robustness
adversarial risk analysis
Seguridad informática
Informática (Informática)
Matemáticas (Matemáticas)
1203.17 Informática
12 Matemáticas
id ES_034d7fc16c3eaa5c31b87945dc5c8d66
oai_identifier_str oai:docta.ucm.es:20.500.14352/7539
network_acronym_str ES
network_name_str España
repository_id_str
spelling Perspectives on Adversarial ClassificationRios Insua, DavidNaveiro, RoiGallego, Víctor004.056004.492Classificationadversarial machine learningsecurityrobustnessadversarial risk analysisSeguridad informáticaInformática (Informática)Seguridad informáticaMatemáticas (Matemáticas)1203.17 Informática12 MatemáticasAdversarial 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.MDPIUniversidad Complutense de Madrid20202020-11-0520202020-11-05journal articlehttp://purl.org/coar/resource_type/c_6501info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/20.500.14352/7539reponame:Docta Complutenseinstname:Universidad Complutense de Madrid (UCM)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Atribución 3.0 Españahttps://creativecommons.org/licenses/by/3.0/es/info:eu-repo/semantics/openAccessoai:docta.ucm.es:20.500.14352/75392026-06-02T12:44:21Z
dc.title.none.fl_str_mv Perspectives on Adversarial Classification
title Perspectives on Adversarial Classification
spellingShingle Perspectives on Adversarial Classification
Rios Insua, David
004.056
004.492
Classification
adversarial machine learning
security
robustness
adversarial risk analysis
Seguridad informática
Informática (Informática)
Seguridad informática
Matemáticas (Matemáticas)
1203.17 Informática
12 Matemáticas
title_short Perspectives on Adversarial Classification
title_full Perspectives on Adversarial Classification
title_fullStr Perspectives on Adversarial Classification
title_full_unstemmed Perspectives on Adversarial Classification
title_sort Perspectives on Adversarial Classification
dc.creator.none.fl_str_mv Rios Insua, David
Naveiro, Roi
Gallego, Víctor
author Rios Insua, David
author_facet Rios Insua, David
Naveiro, Roi
Gallego, Víctor
author_role author
author2 Naveiro, Roi
Gallego, Víctor
author2_role author
author
dc.contributor.none.fl_str_mv Universidad Complutense de Madrid
dc.subject.none.fl_str_mv 004.056
004.492
Classification
adversarial machine learning
security
robustness
adversarial risk analysis
Seguridad informática
Informática (Informática)
Seguridad informática
Matemáticas (Matemáticas)
1203.17 Informática
12 Matemáticas
topic 004.056
004.492
Classification
adversarial machine learning
security
robustness
adversarial risk analysis
Seguridad informática
Informática (Informática)
Seguridad informática
Matemáticas (Matemáticas)
1203.17 Informática
12 Matemáticas
description 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.
publishDate 2020
dc.date.none.fl_str_mv 2020
2020-11-05
2020
2020-11-05
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/20.500.14352/7539
url https://hdl.handle.net/20.500.14352/7539
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Atribución 3.0 España
https://creativecommons.org/licenses/by/3.0/es/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Atribución 3.0 España
https://creativecommons.org/licenses/by/3.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv reponame:Docta Complutense
instname:Universidad Complutense de Madrid (UCM)
instname_str Universidad Complutense de Madrid (UCM)
reponame_str Docta Complutense
collection Docta Complutense
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,300719

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