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Automatic trust calculation for service-oriented systems

机译:面向服务的系统的自动信任计算

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摘要

Among various service providers providing identical or similar services with varying quality of service, trust is essential for service consumers to find the right one. Manually assigning feedback costs much time and suffers from several drawbacks. Only automatic trust calculation is feasible for large-scale service-oriented applications. Therefore an automatic method of trust calculation is proposed. To make the calculation accurate, the Kalman filter is adopted to filter out malicious non-trust quality criterion (NTQC) values instead of malicious trust values. To offer higher detection accuracy, it is further improved by considering the relationship between NTQC values and variances. Since dishonest or inaccurate values can still influence trust values, the similarity between consumers is used to weight data from other consumers. As existing models only used the Euclidean function and ignored others, a collection of distance functions is modified to calculate the similarity. Finally, experiments are carried out to access the robustness of the proposed model. The results show that the improved algorithm can offer higher detection accuracy, and it was discovered that another equation outperformed the Euclidean function.
机译:在提供具有相同或不同服务质量的相同或类似服务的各种服务提供商中,信任对于服务消费者找到正确的服务至关重要。手动分配反馈会花费大量时间,并且存在一些缺点。对于大规模的面向服务的应用程序,只有自动信任计算才可行。因此,提出了一种信任计算的自动方法。为了使计算更加准确,采用卡尔曼滤波器来过滤出恶意的非信任质量标准(NTQC)值,而不是恶意的信任值。为了提供更高的检测精度,可以通过考虑NTQC值和方差之间的关系来进一步改进它。由于不诚实或不正确的值仍会影响信任值,因此,使用方之间的相似性用于权衡来自其他方的数据。由于现有模型仅使用欧几里得函数而忽略了其他函数,因此对距离函数的集合进行了修改以计算相似度。最后,进行实验以获取所提出模型的鲁棒性。结果表明,改进的算法可以提供更高的检测精度,并且发现另一个方程优于欧几里得函数。

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  • 来源
    《Software, IET》 |2014年第3期|134-142|共9页
  • 作者单位

    Faculty of Engineering, Science and the Built Environment, London South Bank University, London SE1 0AA, UK|c|;

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  • 正文语种 eng
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