Grey Model and Polynomial Regression for Identifying Malicious Nodes in MANETs
Autor(a) principal: | |
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Data de Publicação: | 2014 |
Outros Autores: | , , , |
Tipo de documento: | Artigo de conferência |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://hdl.handle.net/11449/183950 |
Resumo: | Nodes positioning is an essential issue for diverse applications in Mobile Ad Hoc Networks (MANETs). However, besides misbehaving nodes that could cause power depletion, MANETs are also susceptible to cyber-attacks, which can make the network unstable and/or unavailable. Therefore, considering the gaps aforementioned, the goal of this paper is to propose a model for identifying malicious/misbehaving nodes by: (1) the use of two forecasting methods (Grey Model and Polynomial Regression); (2) variability analysis; and (3) simulation of fake node positions. The obtained results allow concluding our model has high rate of accuracy for detecting malicious/misbehaving nodes. |
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Repositório Institucional da UNESP |
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Grey Model and Polynomial Regression for Identifying Malicious Nodes in MANETsGrey Theory GM(1,1)Polynomial RegressionMANETmisbehaving node detectionmalicious node identificationprediction modelNodes positioning is an essential issue for diverse applications in Mobile Ad Hoc Networks (MANETs). However, besides misbehaving nodes that could cause power depletion, MANETs are also susceptible to cyber-attacks, which can make the network unstable and/or unavailable. Therefore, considering the gaps aforementioned, the goal of this paper is to propose a model for identifying malicious/misbehaving nodes by: (1) the use of two forecasting methods (Grey Model and Polynomial Regression); (2) variability analysis; and (3) simulation of fake node positions. The obtained results allow concluding our model has high rate of accuracy for detecting malicious/misbehaving nodes.Univ Sao Paulo, LSI POLI, BR-05508 Sao Paulo, BrazilUniv Avignon, CERI LIA, Avignon, FranceUniv Estadual Paulista, Unip, Sao Paulo, BrazilUniv Estadual Paulista, Unip, Sao Paulo, BrazilIeeeUniversidade de São Paulo (USP)Univ AvignonUniversidade Estadual Paulista (Unesp)Silva, Anderson A. A. [UNESP]Pontes, ElvisZhou, FenKofuji, Sergio TakeoIEEE2019-10-03T18:18:36Z2019-10-03T18:18:36Z2014-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject162-1682014 Ieee Global Communications Conference (globecom 2014). New York: Ieee, p. 162-168, 2014.2334-0983http://hdl.handle.net/11449/183950WOS:000369900400027Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPeng2014 Ieee Global Communications Conference (globecom 2014)info:eu-repo/semantics/openAccess2021-10-23T15:54:45Zoai:repositorio.unesp.br:11449/183950Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T14:38:09.437457Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Grey Model and Polynomial Regression for Identifying Malicious Nodes in MANETs |
title |
Grey Model and Polynomial Regression for Identifying Malicious Nodes in MANETs |
spellingShingle |
Grey Model and Polynomial Regression for Identifying Malicious Nodes in MANETs Silva, Anderson A. A. [UNESP] Grey Theory GM(1,1) Polynomial Regression MANET misbehaving node detection malicious node identification prediction model |
title_short |
Grey Model and Polynomial Regression for Identifying Malicious Nodes in MANETs |
title_full |
Grey Model and Polynomial Regression for Identifying Malicious Nodes in MANETs |
title_fullStr |
Grey Model and Polynomial Regression for Identifying Malicious Nodes in MANETs |
title_full_unstemmed |
Grey Model and Polynomial Regression for Identifying Malicious Nodes in MANETs |
title_sort |
Grey Model and Polynomial Regression for Identifying Malicious Nodes in MANETs |
author |
Silva, Anderson A. A. [UNESP] |
author_facet |
Silva, Anderson A. A. [UNESP] Pontes, Elvis Zhou, Fen Kofuji, Sergio Takeo IEEE |
author_role |
author |
author2 |
Pontes, Elvis Zhou, Fen Kofuji, Sergio Takeo IEEE |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
Universidade de São Paulo (USP) Univ Avignon Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Silva, Anderson A. A. [UNESP] Pontes, Elvis Zhou, Fen Kofuji, Sergio Takeo IEEE |
dc.subject.por.fl_str_mv |
Grey Theory GM(1,1) Polynomial Regression MANET misbehaving node detection malicious node identification prediction model |
topic |
Grey Theory GM(1,1) Polynomial Regression MANET misbehaving node detection malicious node identification prediction model |
description |
Nodes positioning is an essential issue for diverse applications in Mobile Ad Hoc Networks (MANETs). However, besides misbehaving nodes that could cause power depletion, MANETs are also susceptible to cyber-attacks, which can make the network unstable and/or unavailable. Therefore, considering the gaps aforementioned, the goal of this paper is to propose a model for identifying malicious/misbehaving nodes by: (1) the use of two forecasting methods (Grey Model and Polynomial Regression); (2) variability analysis; and (3) simulation of fake node positions. The obtained results allow concluding our model has high rate of accuracy for detecting malicious/misbehaving nodes. |
publishDate |
2014 |
dc.date.none.fl_str_mv |
2014-01-01 2019-10-03T18:18:36Z 2019-10-03T18:18:36Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/conferenceObject |
format |
conferenceObject |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
2014 Ieee Global Communications Conference (globecom 2014). New York: Ieee, p. 162-168, 2014. 2334-0983 http://hdl.handle.net/11449/183950 WOS:000369900400027 |
identifier_str_mv |
2014 Ieee Global Communications Conference (globecom 2014). New York: Ieee, p. 162-168, 2014. 2334-0983 WOS:000369900400027 |
url |
http://hdl.handle.net/11449/183950 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
2014 Ieee Global Communications Conference (globecom 2014) |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
162-168 |
dc.publisher.none.fl_str_mv |
Ieee |
publisher.none.fl_str_mv |
Ieee |
dc.source.none.fl_str_mv |
Web of Science reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808128391330660352 |