We propose a decentralized trust management scheme for vehicular networks. The proposed scheme uses a fuzzy logic-based trust evaluation approach to calculate the direct trusts where evaluatees are located within the transmission range of the evaluator. A reinforcement learning-based approach is also employed to estimate the indirect trusts where the behaviors of evaluatees cannot be directly observed. The computer simulations are conducted to show the advantage of the proposed scheme over other baseline approaches.
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We propose a decentralized trust management scheme for vehicular networks. The proposed scheme uses a fuzzy logic-based trust evaluation approach to calculate the direct trusts where evaluatees are located within the transmission range of the evaluator. A reinforcement learning-based approach is also employed to estimate the indirect trusts where the behaviors of evaluatees cannot be directly observed. The computer simulations are conducted to show the advantage of the proposed scheme over other baseline approaches.