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A new direct trust model is proposed.
Both direct trust and indirect trust are taken into consideration when designing the trust management system.
In this model, we estimate the trust degree between nodes from direct trust computation of direct observation and indirect trust computation by neighbors' recommendations.
The algorithm is extended to consider situations in which direct trust does exist between certain participants and those with deadlines for completion.
The model introduces the time decay factor to solve the problem that the trust dynamic change over time, taking into account different transaction amount given different weights, it designs the direct trust calculation method based on service attributes and combining weights, reflecting the direct trust timeliness, rationality.
The developed control system is embedded with a trust evaluation model, designed using a novel adaptation of Markov Games concept into temporal difference learning to compute the direct trust and using a novel heuristic method to integrate the indirect trust.
In this paper, we first design a recommendation-based online social network architecture by incorporating trust information (namely, direct trust and indirect trust), relevance degree and recommended influence value.
Fig. 7 Direct trust calculation Fig. 8 Indirect trust calculation.
We first study the results on direct trust evaluation experiment.
The model uses direct trust to calculate the global trust.
Figure 7: direct trust for different nodes shows the direct trust calculated for random node 5, 20, 30 and 40 at a maximum time period of 500 s.
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