• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

计算机工程与科学 ›› 2021, Vol. 43 ›› Issue (09): 1574-1583.

• 计算机网络与信息安全 • 上一篇    下一篇

一种边缘设备动态信任度的评估模型

赵国生1,王甜甜1,王健2   

  1. (1.哈尔滨师范大学计算机科学与信息工程学院,黑龙江 哈尔滨 150025;

    2.哈尔滨理工大学计算机科学与技术学院,黑龙江 哈尔滨 150080)

  • 收稿日期:2019-11-21 修回日期:2020-07-27 接受日期:2021-09-25 出版日期:2021-09-25 发布日期:2021-09-27
  • 基金资助:
    国家自然科学基金(61202458,61403109);黑龙江省自然科学基金(LH2020F034)

A dynamic trust evaluation model for edge devices

ZHAO Guo-sheng1,WANG Tian-tian1,WANG Jian2   

  1. (1.College of Computer Science and Information Engineering,Harbin Normal University,Harbin 150025;

    2.School of Computer Science and Technology,Harbin University of Science and Technology,Harbin 150080,China)

  • Received:2019-11-21 Revised:2020-07-27 Accepted:2021-09-25 Online:2021-09-25 Published:2021-09-27

摘要: 面向边缘计算环境中设备信任度评估的准确性和时间开销等问题,提出一种边缘设备动态信任度评估模型—DTEM。首先,利用时间退化因子表达直接信任度时效性,引入满意度函数修正贝叶斯方程,并结合激励机制评估边缘设备间的直接信任度。其次,利用改进的灰关联分析法确定指标权重,解决了间接信任度评估过程中推荐设备权重的问题。最后,通过信息熵融合直接信任度和间接信任度得出设备综合信任值,同时利用动态更新因子,动态更新综合信任值。仿真分析表明,相比RFSN模型,DTEM在检测恶意设备中误检率平均降低5.7%,设备间交互成功率平均提升4.1%,同时验证了DTEM在时间开销方面优于FHTM模型和RFSN模型,能够更准确高效地评估边缘设备的信任度。


关键词: 边缘计算, 信任度评估, 时间退化因子, 灰关联分析

Abstract: Aiming at the accuracy and time overhead of device trust evaluation in edge computing environment, a dynamic trust evaluation model for edge devices is proposed. Firstly, the time-degradation factor is used to express the degree of direct trust invalidity, the satisfaction function is introduced to modify the Bayesian equation, and the incentive mechanism is used to evaluate the direct trust between edge devices. Secondly, the improved grey correlation analysis method is used to determine the index weight to solve the problem of recommending equipment weight in the process of indirect trust evaluation. Finally, through the information entropy fusion of direct trust and indirect trust, the comprehensive trust value of the device is obtained, and the dynamic update factor is used to dynamically update the integrated trust value. The simulation analysis shows that, compared with the RFSN model, the proposed model can reduce the false detection rate of malicious devices by 5.7% on average, and increase the inter-device interaction success rate by 4.1%. At the same time, it is verified that the trust evaluation model is superior to the FHTM model and the RFSN model in terms of time overhead, which can more accurately and efficiently evaluate the trust of edge devices.


Key words: edge computing, trust evaluation, time-degradation factor, grey relational analysis