| Popis: |
With the development of 5G and artificial intelligence, the security of Cloud-Edge-End Collaboration (CEEC) networks becomes an increasingly prominent issue due to the complexity of the environment, real-time variability and diversity of edge devices in CEEC networks. In this paper, we design a lightweight fuzzy collaborative trust evaluation model (LFCTEM) for edge devices, and calculate the trust values of edge devices by fuzzifying trust factors. To alleviate the selfish behavior of edge devices, this paper introduces an incentive mechanism in the trust evaluation model, and achieves a long-term incentive effect by designing an incentive negative decay mechanism, which enhances the initiative of collaboration and improves the interference resistance of CEEC networks. We verify the performance of LFCTEM through simulation experiments. Compared with other methods, our model enhances the detection rate of malicious edge devices by 19.11%, which improves the reliability of the CEEC trust environment. Meanwhile, our model reduces the error detection rate of edge devices by 16.20%, thus alleviating error reporting of the CEEC trust environment. |
