Sybil Attack Detection in VANETs using an AdaBoost Classifier-Reference-Cited by-同舟云学术

Sybil Attack Detection in VANETs using an AdaBoost Classifier

Published:2022-05-30 Issue: Volume: Page:
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Container-title:2022 International Wireless Communications and Mobile Computing (IWCMC)
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Author:

Laouiti Dhia Eddine¹,Ayaida Marwane¹,Messai Nadhir¹,Najeh Sameh²,Najjar Leila²,Chaabane Ferdaous²

Affiliation:

1. CReSTIC, Campus Moulin de La Housse Universite de Reims Champagne-Ardenne,Reims,France

2. University of Carthage,Higher School of Communications of Tunis, COSIM Research Lab,Tunis,Tunisia

Funder

CAMPUS France

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9823957/9824097/09824974.pdf?arnumber=9824974

Reference10 articles.

1. An Effective Misbehavior Detection Model Using Artificial Neural Network for Vehicular Ad Hoc Network Applications;fuad;2017 IEEE Conference on Application Information and Network Security (AINS) AINS,2017

2. A Macroscopic Traffic Model-based Approach for Sybil Attack Detection in VANETs

3. VeReMi Extension: A Dataset for Com-parable Evaluation of Misbehavior Detection in VANETs;joseph;ICC 2020 – 2020 IEEE Int Conf Commun (ICC),2020

4. Sybil Attack Detection and Prevention in VANETs: A Survey

5. Collaborative Security Attack Detection in Software-Defined Ve-hicular Networks;myeongsu;2017 19th Asia-Pacific Network Operations and Management Symposium,0

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