基于可选择的信任规则基础的工业互联网安全评估模型.
Qingqing Yang1, Shiming Li1, Yuhe Wang1
1College of Computer Science and Information Engineering, Harbin Normal University, Harbin 150025, China.
Sensors (Basel, Switzerland)
|December 17, 2024
概括
本研究引入了一个基于信任规则的安全评估模型,用于工业互联网,增强网络安全. 该模型使用选择性建模和优化算法来提高有限数据的准确性.
科学领域:
- 计算机科学 计算机科学
- 网络安全 网络安全
- 工业互联网 工业互联网 工业互联网
背景情况:
- 网络安全对于工业互联网生产环境至关重要.
- 现有的模型面临着数据不足或质量不佳的挑战.
研究的目的:
- 为工业互联网提出基于信任规则的安全评估模型.
- 加强网络安全并减轻对生产环境的影响.
主要方法:
- 开发了一个针对工业互联网量身定制的选择性建模定义.
- 引入了可选择信念规则基础 (BRB-s) 模型评估过程.
- 设计了一个参数优化方法,使用选择协差矩阵自适应进化策略 (S-CMA-ES) 算法.
主要成果:
- 与S-CMA-ES优化相结合的BRB-s模型取得了更好的评估结果.
- 有效地解决了由于数据限制而导致的模型精度降低的问题.
- 实验性比较验证了模型的准确性和算法的有效性.
结论:
- 拟议的工业互联网网络安全评估模型显示了高准确度.
- 在参数调整方面,S-CMA-ES优化算法是可行的和有效的.
- 该方法增强了工业互联网安全性和数据驱动的决策.
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