Vehicular Social Networks (VSNs) is an emerging communication paradigm, derived by merging the concepts of Online Social Networks (OSNs) and Vehicular Ad-hoc Networks (VANETs). Due to the lack of robust authentication mechanisms, social-based vehicular applications are vulnerable to numerous attacks including the generation of sybil entities in the networks. We address this important issue in vehicular crowdsourcing campaigns where sybils are usually employed to increase their influence and worsen the functioning of the system. In particular, we propose a novel User Recruitment Policy (URP) that, after extracting the participants within the event radius of a crowdsourcing campaign, detects and filters out the sybil vehicles by using a novel sybil detection approach, called SybilDriver. This technique combines the advantages of VANETs and OSNs by means of an innovative concept of proximity graph obtained from the physical vehicular network, in conjunction with a community detection and Random Forest techniques adopted in the OSN domain. Detailed experimental evaluations demonstrate the effectiveness of our approach and also show that it outperforms existing state-of-the-art methods typically used in the OSNs.1

Concone F., De Vita F., Pratap A., Bruneo D., Lo Re G., Das K. S. (2021). A Novel Recruitment Policy to Defend against Sybils in Vehicular Crowdsourcing. In Proceedings - 2021 IEEE International Conference on Smart Computing, SMARTCOMP 2021 (pp. 105-112). Institute of Electrical and Electronics Engineers Inc. [10.1109/SMARTCOMP52413.2021.00035].

A Novel Recruitment Policy to Defend against Sybils in Vehicular Crowdsourcing

Concone F.
Primo
;
Lo Re G.;
2021-01-01

Abstract

Vehicular Social Networks (VSNs) is an emerging communication paradigm, derived by merging the concepts of Online Social Networks (OSNs) and Vehicular Ad-hoc Networks (VANETs). Due to the lack of robust authentication mechanisms, social-based vehicular applications are vulnerable to numerous attacks including the generation of sybil entities in the networks. We address this important issue in vehicular crowdsourcing campaigns where sybils are usually employed to increase their influence and worsen the functioning of the system. In particular, we propose a novel User Recruitment Policy (URP) that, after extracting the participants within the event radius of a crowdsourcing campaign, detects and filters out the sybil vehicles by using a novel sybil detection approach, called SybilDriver. This technique combines the advantages of VANETs and OSNs by means of an innovative concept of proximity graph obtained from the physical vehicular network, in conjunction with a community detection and Random Forest techniques adopted in the OSN domain. Detailed experimental evaluations demonstrate the effectiveness of our approach and also show that it outperforms existing state-of-the-art methods typically used in the OSNs.1
2021
Settore ING-INF/05 - Sistemi Di Elaborazione Delle Informazioni
978-1-6654-1252-0
Concone F., De Vita F., Pratap A., Bruneo D., Lo Re G., Das K. S. (2021). A Novel Recruitment Policy to Defend against Sybils in Vehicular Crowdsourcing. In Proceedings - 2021 IEEE International Conference on Smart Computing, SMARTCOMP 2021 (pp. 105-112). Institute of Electrical and Electronics Engineers Inc. [10.1109/SMARTCOMP52413.2021.00035].
File in questo prodotto:
File Dimensione Formato  
A_Novel_Recruitment_Policy_to_Defend_against_Sybils_in_Vehicular_Crowdsourcing.pdf

Solo gestori archvio

Descrizione: Articolo principale completo di indice
Tipologia: Versione Editoriale
Dimensione 4.52 MB
Formato Adobe PDF
4.52 MB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/524956
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 2
  • ???jsp.display-item.citation.isi??? 2
social impact