Collaborative Learning Based Sybil Attack Detection in Vehicular AD-HOC Networks (VANETS).

Azam, Sofia; Bibi, Maryum; Riaz, Rabia; Rizvi, Sanam Shahla; Kwon, Se Jin

Azam, Sofia; Bibi, Maryum; Riaz, Rabia; Rizvi, Sanam Shahla; Kwon, Se Jin.

Afiliação

Azam S; Department of Computer Science and IT, University of Azad Jammu and Kashmir, Muzaffarabad 13100, CO, Pakistan.
Bibi M; Department of Computer Science and IT, University of Azad Jammu and Kashmir, Muzaffarabad 13100, CO, Pakistan.
Riaz R; Department of Computer Science and IT, University of Azad Jammu and Kashmir, Muzaffarabad 13100, CO, Pakistan.
Rizvi SS; Raptor Interactive (Pty) Ltd., Eco Boulevard, Witch Hazel Ave, Centurion 0157, South Africa.
Kwon SJ; Department of AI Software, Kangwon National University, Samcheok 25913, Korea.

Sensors (Basel) ; 22(18)2022 Sep 13.

Article em En | MEDLINE | ID: mdl-36146282

Assuntos

Redes de Comunicação de Computadores; Práticas Interdisciplinares; Teorema de Bayes; Análise por Conglomerados

Palavras-chave

VANET; machine learning; sybil attack; vehicular ad hoc network

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Redes de Comunicação de Computadores / Práticas Interdisciplinares Tipo de estudo: Diagnostic_studies / Prognostic_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article

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