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基于重方法的自适应信任评估模型,用于检测终端过程.

Tao Li1,2,3, Yanyi Zhang1

  • 1School of Cyber Science and Engineering, Southeast University, Nanjing 211189, China.

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本研究介绍了PB-ATEM,这是用于遥感 (RS) 终端的自适应性信任评估模型. 它通过结合直接和相互信任值来提高检测准确度和恶意进程识别.

关键词:
自动相关性自动相关性重量方法的重方法.k-意味着集群分析.过程安全 过程安全 过程安全信任评价信任评价的评估值得信赖的信任价值

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科学领域:

  • 计算机科学 计算机科学
  • 信息安全 信息安全
  • 遥感 遥感 遥感 遥感

背景情况:

  • 遥感 (RS) 终端由于其无人监督的性质,容易受到攻击.
  • 现有的RS传感终端的信任评估模型在检测恶意进程方面性能和精度较低.

研究的目的:

  • 提出一种适应性信任评估模型 (PB-ATEM) 用于检测终端过程.
  • 提高远程传感系统中识别恶意进程的准确性和速度.

主要方法:

  • 开发PB-ATEM使用重量方法和k-means集群.
  • 内置的直接信任 (动态自关联,奖励/惩罚) 和相互信任的价值.
  • 综合信任评分的权重直接和互惠信任值.

主要成果:

  • PB-ATEM 展示了对恶意进程的快速响应.
  • 与现有方法相比,拟议的模型实现了更高的检测精度.
  • 在识别恶意传感终端进程方面,PB-ATEM表现出更好的能力.

结论:

  • PB-ATEM提供了一种更有效的解决方案,用于对遥感终端的信任评估.
  • 该模型的自适应性和结合的信任指标提高了对恶意活动的安全性.
  • 这种方法显著提高了无人远程传感系统的可靠性和安全性.