Belief revision in structured probabilistic argumentation: Model and application to cyber security
- Autores
- Shakarian, Paulo; Simari, Gerardo; Moores, Geoffrey; Paulo, Damon; Parsons, Simon; Falappa, Marcelo Alejandro; Aleali, Ashkan
- Año de publicación
- 2016
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- In real-world applications, knowledge bases consisting of all the available information for a specific domain, along with the current state of affairs, will typically contain contradictory data, coming from different sources, as well as data with varying degrees of uncertainty attached. An important aspect of the effort associated with maintaining such knowledge bases is deciding what information is no longer useful; pieces of information may be outdated; may come from sources that have recently been discovered to be of low quality; or abundant evidence may be available that contradicts them. In this paper, we propose a probabilistic structured argumentation framework that arises from the extension of Presumptive Defeasible Logic Programming (PreDeLP) with probabilistic models, and argue that this formalism is capable of addressing these basic issues. The formalism is capable of handling contradictory and uncertain data, and we study non-prioritized belief revision over probabilistic PreDeLP programs that can help with knowledge-base maintenance. For belief revision, we propose a set of rationality postulates — based on well-known ones developed for classical knowledge bases — that characterize how these belief revision operations should behave, and study classes of operators along with theoretical relationships with the proposed postulates, including representation theorems stating the equivalence between classes of operators and their associated postulates. We then demonstrate how our framework can be used to address the attribution problem in cyber security/cyber warfare.
Fil: Shakarian, Paulo. Arizona State University; Estados Unidos
Fil: Simari, Gerardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; Argentina
Fil: Moores, Geoffrey. U.S. Military Academy; Estados Unidos
Fil: Paulo, Damon. U.S. Military Academy; Estados Unidos
Fil: Parsons, Simon. University of Liverpool; Reino Unido
Fil: Falappa, Marcelo Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; Argentina
Fil: Aleali, Ashkan. Arizona State University; Estados Unidos - Materia
-
ARGUMENTATION
BELIEF REVISION
CYBER SECURITY
PROBABILISTIC REASONING - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
- Repositorio
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/51361
Ver los metadatos del registro completo
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Belief revision in structured probabilistic argumentation: Model and application to cyber securityShakarian, PauloSimari, GerardoMoores, GeoffreyPaulo, DamonParsons, SimonFalappa, Marcelo AlejandroAleali, AshkanARGUMENTATIONBELIEF REVISIONCYBER SECURITYPROBABILISTIC REASONINGhttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1In real-world applications, knowledge bases consisting of all the available information for a specific domain, along with the current state of affairs, will typically contain contradictory data, coming from different sources, as well as data with varying degrees of uncertainty attached. An important aspect of the effort associated with maintaining such knowledge bases is deciding what information is no longer useful; pieces of information may be outdated; may come from sources that have recently been discovered to be of low quality; or abundant evidence may be available that contradicts them. In this paper, we propose a probabilistic structured argumentation framework that arises from the extension of Presumptive Defeasible Logic Programming (PreDeLP) with probabilistic models, and argue that this formalism is capable of addressing these basic issues. The formalism is capable of handling contradictory and uncertain data, and we study non-prioritized belief revision over probabilistic PreDeLP programs that can help with knowledge-base maintenance. For belief revision, we propose a set of rationality postulates — based on well-known ones developed for classical knowledge bases — that characterize how these belief revision operations should behave, and study classes of operators along with theoretical relationships with the proposed postulates, including representation theorems stating the equivalence between classes of operators and their associated postulates. We then demonstrate how our framework can be used to address the attribution problem in cyber security/cyber warfare.Fil: Shakarian, Paulo. Arizona State University; Estados UnidosFil: Simari, Gerardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; ArgentinaFil: Moores, Geoffrey. U.S. Military Academy; Estados UnidosFil: Paulo, Damon. U.S. Military Academy; Estados UnidosFil: Parsons, Simon. University of Liverpool; Reino UnidoFil: Falappa, Marcelo Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; ArgentinaFil: Aleali, Ashkan. Arizona State University; Estados UnidosSpringer2016-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/51361Shakarian, Paulo; Simari, Gerardo; Moores, Geoffrey; Paulo, Damon; Parsons, Simon; et al.; Belief revision in structured probabilistic argumentation: Model and application to cyber security; Springer; Annals of Mathematics and Artificial Intelligence; 78; 3-4; 12-2016; 259-3011012-2443CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1007/s10472-015-9483-5info:eu-repo/semantics/altIdentifier/url/https://link.springer.com/article/10.1007%2Fs10472-015-9483-5info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:45:37Zoai:ri.conicet.gov.ar:11336/51361instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 09:45:37.962CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
dc.title.none.fl_str_mv |
Belief revision in structured probabilistic argumentation: Model and application to cyber security |
title |
Belief revision in structured probabilistic argumentation: Model and application to cyber security |
spellingShingle |
Belief revision in structured probabilistic argumentation: Model and application to cyber security Shakarian, Paulo ARGUMENTATION BELIEF REVISION CYBER SECURITY PROBABILISTIC REASONING |
title_short |
Belief revision in structured probabilistic argumentation: Model and application to cyber security |
title_full |
Belief revision in structured probabilistic argumentation: Model and application to cyber security |
title_fullStr |
Belief revision in structured probabilistic argumentation: Model and application to cyber security |
title_full_unstemmed |
Belief revision in structured probabilistic argumentation: Model and application to cyber security |
title_sort |
Belief revision in structured probabilistic argumentation: Model and application to cyber security |
dc.creator.none.fl_str_mv |
Shakarian, Paulo Simari, Gerardo Moores, Geoffrey Paulo, Damon Parsons, Simon Falappa, Marcelo Alejandro Aleali, Ashkan |
author |
Shakarian, Paulo |
author_facet |
Shakarian, Paulo Simari, Gerardo Moores, Geoffrey Paulo, Damon Parsons, Simon Falappa, Marcelo Alejandro Aleali, Ashkan |
author_role |
author |
author2 |
Simari, Gerardo Moores, Geoffrey Paulo, Damon Parsons, Simon Falappa, Marcelo Alejandro Aleali, Ashkan |
author2_role |
author author author author author author |
dc.subject.none.fl_str_mv |
ARGUMENTATION BELIEF REVISION CYBER SECURITY PROBABILISTIC REASONING |
topic |
ARGUMENTATION BELIEF REVISION CYBER SECURITY PROBABILISTIC REASONING |
purl_subject.fl_str_mv |
https://purl.org/becyt/ford/1.2 https://purl.org/becyt/ford/1 |
dc.description.none.fl_txt_mv |
In real-world applications, knowledge bases consisting of all the available information for a specific domain, along with the current state of affairs, will typically contain contradictory data, coming from different sources, as well as data with varying degrees of uncertainty attached. An important aspect of the effort associated with maintaining such knowledge bases is deciding what information is no longer useful; pieces of information may be outdated; may come from sources that have recently been discovered to be of low quality; or abundant evidence may be available that contradicts them. In this paper, we propose a probabilistic structured argumentation framework that arises from the extension of Presumptive Defeasible Logic Programming (PreDeLP) with probabilistic models, and argue that this formalism is capable of addressing these basic issues. The formalism is capable of handling contradictory and uncertain data, and we study non-prioritized belief revision over probabilistic PreDeLP programs that can help with knowledge-base maintenance. For belief revision, we propose a set of rationality postulates — based on well-known ones developed for classical knowledge bases — that characterize how these belief revision operations should behave, and study classes of operators along with theoretical relationships with the proposed postulates, including representation theorems stating the equivalence between classes of operators and their associated postulates. We then demonstrate how our framework can be used to address the attribution problem in cyber security/cyber warfare. Fil: Shakarian, Paulo. Arizona State University; Estados Unidos Fil: Simari, Gerardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; Argentina Fil: Moores, Geoffrey. U.S. Military Academy; Estados Unidos Fil: Paulo, Damon. U.S. Military Academy; Estados Unidos Fil: Parsons, Simon. University of Liverpool; Reino Unido Fil: Falappa, Marcelo Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; Argentina Fil: Aleali, Ashkan. Arizona State University; Estados Unidos |
description |
In real-world applications, knowledge bases consisting of all the available information for a specific domain, along with the current state of affairs, will typically contain contradictory data, coming from different sources, as well as data with varying degrees of uncertainty attached. An important aspect of the effort associated with maintaining such knowledge bases is deciding what information is no longer useful; pieces of information may be outdated; may come from sources that have recently been discovered to be of low quality; or abundant evidence may be available that contradicts them. In this paper, we propose a probabilistic structured argumentation framework that arises from the extension of Presumptive Defeasible Logic Programming (PreDeLP) with probabilistic models, and argue that this formalism is capable of addressing these basic issues. The formalism is capable of handling contradictory and uncertain data, and we study non-prioritized belief revision over probabilistic PreDeLP programs that can help with knowledge-base maintenance. For belief revision, we propose a set of rationality postulates — based on well-known ones developed for classical knowledge bases — that characterize how these belief revision operations should behave, and study classes of operators along with theoretical relationships with the proposed postulates, including representation theorems stating the equivalence between classes of operators and their associated postulates. We then demonstrate how our framework can be used to address the attribution problem in cyber security/cyber warfare. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-12 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
format |
article |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
http://hdl.handle.net/11336/51361 Shakarian, Paulo; Simari, Gerardo; Moores, Geoffrey; Paulo, Damon; Parsons, Simon; et al.; Belief revision in structured probabilistic argumentation: Model and application to cyber security; Springer; Annals of Mathematics and Artificial Intelligence; 78; 3-4; 12-2016; 259-301 1012-2443 CONICET Digital CONICET |
url |
http://hdl.handle.net/11336/51361 |
identifier_str_mv |
Shakarian, Paulo; Simari, Gerardo; Moores, Geoffrey; Paulo, Damon; Parsons, Simon; et al.; Belief revision in structured probabilistic argumentation: Model and application to cyber security; Springer; Annals of Mathematics and Artificial Intelligence; 78; 3-4; 12-2016; 259-301 1012-2443 CONICET Digital CONICET |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/doi/10.1007/s10472-015-9483-5 info:eu-repo/semantics/altIdentifier/url/https://link.springer.com/article/10.1007%2Fs10472-015-9483-5 |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ |
dc.format.none.fl_str_mv |
application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
Springer |
publisher.none.fl_str_mv |
Springer |
dc.source.none.fl_str_mv |
reponame:CONICET Digital (CONICET) instname:Consejo Nacional de Investigaciones Científicas y Técnicas |
reponame_str |
CONICET Digital (CONICET) |
collection |
CONICET Digital (CONICET) |
instname_str |
Consejo Nacional de Investigaciones Científicas y Técnicas |
repository.name.fl_str_mv |
CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas |
repository.mail.fl_str_mv |
dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar |
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1842268744386084864 |
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13.13397 |