Misbehavior Detection in Connected Vehicle: Pre-Bayesian Majority Game Framework

Adil Attiaoui, Adil Attiaoui, Mouna Elmachkour, Abdellatif Kobbane, Marwane Ayaida

2025

Abstract

Ephemeral networks, such as vehicular ad hoc networks, face significant security challenges due to their transient nature and susceptibility to malicious nodes. Traditional trust mechanisms often struggle with dynamic topologies and short-lived interactions, particularly when adversarial nodes spread misinformation. This paper proposes a dual-game theoretical framework combining pre-Bayesian belief updates with majority voting to enhance collaborative misbehavior detection in decentralized vehicular networks. The approach models node interactions through two sequential games: a pre-Bayesian game where nodes assess information credibility based on individual beliefs, followed by a majority game that aggregates collective decisions to refine trust evaluations. Simulations across scenarios with varying malicious node proportions demonstrate the framework’s adaptability, showing consistent belief convergence toward accurate classifications despite increased adversarial influence. Results indicate robust performance even when 40% of nodes exhibit malicious behavior, though convergence delays highlight challenges in highly adversarial environments. The study underscores the importance of maintaining benign node majorities for system stability and suggests future integrations with machine learning for scalability. This work provides a foundation for secure, real-time decision-making in applications requiring reliable ephemeral networks, such as connected vehicle systems.

Paper Citation

in Harvard Style

Attiaoui A., Elmachkour M., Kobbane A. and Ayaida M. (2025). Misbehavior Detection in Connected Vehicle: Pre-Bayesian Majority Game Framework. In Proceedings of the 11th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS; ISBN 978-989-758-745-0, SciTePress, pages 529-536. DOI: 10.5220/0013359100003941

in Bibtex Style

@conference{vehits25,
author={Adil Attiaoui and Mouna Elmachkour and Abdellatif Kobbane and Marwane Ayaida},
title={Misbehavior Detection in Connected Vehicle: Pre-Bayesian Majority Game Framework},
booktitle={Proceedings of the 11th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS},
year={2025},
pages={529-536},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013359100003941},
isbn={978-989-758-745-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS
TI - Misbehavior Detection in Connected Vehicle: Pre-Bayesian Majority Game Framework
SN - 978-989-758-745-0
AU - Attiaoui A.
AU - Elmachkour M.
AU - Kobbane A.
AU - Ayaida M.
PY - 2025
SP - 529
EP - 536
DO - 10.5220/0013359100003941
PB - SciTePress