# Evaluating Reputation Management Schemes of Internet of Vehicles based on Evolutionary Game Theory

arXiv: https://arxiv.org/abs/1902.04667 · HTML: https://mlsanity.com/paper/1902.04667/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 Feb 2019.

## Built on by (most cited first, 3 of 3)

- [An Evolutionary Game based Secure Clustering Protocol with Fuzzy Trust Evaluation and Outlier Detection for Wireless Sensor Networks](https://mlsanity.com/paper/2207.10282/) (2022)
- [PWG-IDS: An Intrusion Detection Model for Solving Class Imbalance in IIoT Networks Using Generative Adversarial Networks](https://mlsanity.com/paper/2110.03445/) (2021)
- [Enhancing Trust Management System for Connected Autonomous Vehicles Using Machine Learning Methods: A Survey](https://mlsanity.com/paper/2505.07882/) (2025)

## Abstract (arXiv)

Conducting reputation management is very important for Internet of vehicles. However, most of the existing researches evaluate the effectiveness of their schemes with settled attacking behaviors in their simulation which cannot represent the scenarios in reality. In this paper, we propose to consider dynamical and diversity attacking strategies in the simulation of reputation management scheme evaluation. To that end, we apply evolutionary game theory to model the evolution process of malicious users' attacking strategies, and discuss the methodology of the evaluation simulations. We further apply our evaluation method to a reputation management scheme with multiple utility functions, and discuss the evaluation results. The results indicate that our evaluation method is able to depict the evolving process of the dynamic attacking strategies in a vehicular network, and the final state of the simulation could be used to quantify the protection effectiveness of the reputation management scheme.