On a security scheme against collusive attacks in vehicular ad hoc networks

Na Fan, Chase Wu, Slimane Benabdallah, Jialong Li, Yuxin Gao, Qinglong Wang

Research output: Contribution to journalArticlepeer-review

Abstract

Vehicular Ad Hoc Networks (VANETs) offer a promising solution to bring drivers comfortable driving experiences and also improve road safety in intelligent transportation systems, but also faces many security issues. Collusive attack is one of the most challenging threats in VANETs because it violates the fundamental assumption made by VANET-based applications that all received information be correct and trustworthy. Collusive attackers can not only generate and send false or forged messages, but also purposely manipulate the reputation value of normal or malicious vehicular nodes. To address these issues, we analyze the behaviors characteristics of collusive attacks and propose a generic, lightweight, and fully distributed detection scheme against collusive attacks in VANETs. This scheme integrates two methods to identify different collusive attacks for fraud reputation and fraud message, respectively, as well as an incentive method to restrain collusive nodes. Simulation-based experiments are conducted and the results illustrate the superiority of the proposed security scheme over state-of-the-art methods.

Original languageEnglish (US)
Article number100821
JournalVehicular Communications
Volume49
DOIs
StatePublished - Oct 2024
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Communication
  • Automotive Engineering
  • Electrical and Electronic Engineering

Keywords

  • Collusive attacks
  • Incentive model
  • Security scheme
  • Vehicular networks

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