Trust evaluation model for electric power mobile Internet environment based on graph and semantic time window

Lili Yang; Jun Han; Wenxi Long; Yu Zhang

doi:10.1117/12.2683566

26 June 2023 Trust evaluation model for electric power mobile Internet environment based on graph and semantic time window

Lili Yang, Jun Han, Wenxi Long, Yu Zhang

Author Affiliations +

Proceedings Volume 12721, Second International Symposium on Computer Applications and Information Systems (ISCAIS 2023); 1272105 (2023) https://doi.org/10.1117/12.2683566
Event: 2023 2nd International Symposium on Computer Applications and Information Systems (ISCAIS 2023), 2023, Chengdu, China

Abstract

At present, the time window setting of the multi-entity continuous trust evaluation model in the power mobile Internet environment lacks adaptability. The semantic retention of time series data is significant to time window setting. A trust evaluation model based on the graph model and semantic time window may provide a solution. Firstly, we analyze the entity interactions in the electric power mobile network environment and construct a global trust path diagram by combining the entropy scoring results of evidence data in this paper. Secondly, a semantic time window algorithm is proposed by combining the parameter-seeking process of the sequential data compression algorithm. Finally, update the trust value dynamically by combining the number of feature changes of entities in the global trust path graph and the semantic time window. Simulation experiments are conducted to analyze the trust value updating algorithm based on the graph model and semantic time window proposed in this paper. The experimental results show that the algorithm is feasible and accurate.

Citation Download Citation

Lili Yang, Jun Han, Wenxi Long, and Yu Zhang "Trust evaluation model for electric power mobile Internet environment based on graph and semantic time window", Proc. SPIE 12721, Second International Symposium on Computer Applications and Information Systems (ISCAIS 2023), 1272105 (26 June 2023); https://doi.org/10.1117/12.2683566

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