Abstract
Trust management in a decentralized vehicular network, such as vehicular ad hoc network, is particularly challenging due to the lack of centralized communication infrastructure and a fast varying feature of the vehicular environment. In this paper, we propose a decentralized trust management scheme for vehicular networks. The proposed scheme uses a fuzzy logic-based trust calculation approach to evaluate the direct trust where trustee nodes are located within the transmission range of a trustor node. A reinforcement learning-based approach is also employed to estimate the indirect trust where the behaviors of trustee cannot be observed directly. The extensive simulations are conducted to show the advantage of the proposed scheme over other baseline approaches.
Original language | English |
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Article number | 8616885 |
Pages (from-to) | 15980-15988 |
Number of pages | 9 |
Journal | IEEE Access |
Volume | 7 |
DOIs | |
Publication status | Published - 17 Jan 2019 |
MoE publication type | Not Eligible |
Keywords
- fuzzy logic
- Q-learning
- trust management
- vehicular ad hoc networks