کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
403891 677366 2012 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Context-sensitive trust computing in distributed environments
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Context-sensitive trust computing in distributed environments
چکیده انگلیسی

With deep and broad applications in distributed computing, how to promote cooperation between entities becomes more and more important. Trust has been proven to be essential to enforce cooperative behaviors in distributed environments. To build trust relationship depends on some factors, such as context, behaviors, and experiences, and it is more challenging to accurately measure them. In this paper, we present a context-sensitive trust computing model to address this problem. Firstly, a trust space with fit-degree is defined based on the contextual information and a context-sensitive fit-law is proposed to judge the abilities of entities. Then, a trust computing model is proposed and followed by an expatiated dynamics trust analysis. Next, considering a new entity without trustworthiness can almost not do anything, we further present an algorithm of initial trustworthiness based on the new entity’s abilities. The entity’s trustworthiness is divided into the initial trustworthiness, the direct trustworthiness, and the recommended trustworthiness. Based on the trustworthiness obtained by the trust fusion algorithm, a mechanism of making trust decision is presented to promote cooperation. The simulation results show that our model can enhance the cooperation among entities. The malicious behaviors can be controlled because of the trustworthiness threshold of services. As such, the honest peers can be incentive, the network stability can be promoted, and the extent of network security can be improved. The proposed dynamic trust computing model is proven to be reasonable, practical, comparable, and workable in distributed services environments.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Knowledge-Based Systems - Volume 28, April 2012, Pages 105–114
نویسندگان
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