Dynamic trust evaluation in open networks. Issue 4 (1st October 2016)

• Record Type: Journal Article
• Authors: Zhao, Bin; He, Jingsha; Zhang, Yixuan; Liu, Gongzheng; Zhai, Peng; Huang, Na; Liu, Ruohong
• Is Part Of: Intelligent automation & soft computing. Volume 22:Issue 4(2016)
• Page Start: 631
• Page End: 638
• Publication Date: 2016-10-01
• Subjects: Open networks -- trust -- trust evaluation -- balanced weight -- dynamic; Artificial intelligence -- Periodicals; Intelligent control systems -- Periodicals; 003.5
• DOI: 10.1080/10798587.2016.1167438
• Languages: English
• ISSNs: 1079-8587

Abstract

Abstract: Trust has been widely used as an effective means of dealing with security issues in open networks. By taking into consideration of the requirement on dynamic adaptability and incorporating the factors of insufficient conglomerate and incentive mechanisms in trust evaluation, we propose in this paper a dynamic trust evaluation model based on multiple factors that is suitable for open networks. In the proposed model, trust evaluation takes into consideration of direct trust that includes historical information to improve accuracy and recommendation trust that includes a bonus-penalty factor and the reliability of evaluation to improve reliability and efficiency. The calculation of integrated trust relies on solving the problem of determining the weights between direct trust and recommendation trust, resulting in a balanced weight factor being introduced into trust evaluation. In the interactions between network entities, the balanced weight factor changes dynamically as the interactions continue between the entities to make trust evaluation dynamically adaptable. Experimental results show that the proposed method can resist attacks from hostile entities, lower the influence of inaccurate or false recommendations from hostile entities and improve the accuracy of trust evaluation.