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相关实验视频

Updated: Sep 17, 2025

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使用EfficientNet的物联网云环境的增强安全性和增强的足球队训练算法.

Jian Cui1, Lan Shi2, Ahmed Alkhayyat3

  • 1College of Physical Education Science, Anshan Normal University, Liaoning, Anshan, 114000, China. cuijan021004@163.com.

Scientific reports
|July 2, 2025
PubMed
概括
此摘要是机器生成的。

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本研究介绍了一种EfficientNet/EFTTA模型,用于物联网 (IoT) 云环境中的高级入侵检测. 这种新的方法通过准确识别网络威胁,以超过98.56%的准确度显著提高了安全性.

科学领域:

  • 网络安全 网络安全
  • 人工智能的人工智能
  • 云计算 云计算 云计算 云计算

背景情况:

  • 物联网 (IoT) 设备的扩散扩大了物联网云环境中的攻击表面.
  • 保护这些日益复杂的系统免受各种网络威胁是一个重大挑战.

研究的目的:

  • 为物联网云环境开发一个创新的入侵检测系统.
  • 提高物联网网络中异常和入侵检测的准确性和效率.

主要方法:

  • 集成EfficientNet,一个深度学习模型,与增强的足球队训练算法 (EFTTA),一个metaheuristic优化技术.
  • 使用标准数据集 (NSL-KDD和BoT-IoT) 的性能评估和与现有的入侵检测方法进行比较.

主要成果:

  • 拟议的EfficientNet/EFTTA模型在与现有技术相比显示出更高的性能.
  • 实现了高准确率:在NSL-KDD上超过98.56%,在BoT-IoT数据集上达到99.1%.
  • 显示在物联网云基础设施内识别异常和入侵的增强能力.

结论:

  • EfficientNet/EFTTA模型为保护物联网云基础设施提供了一个有希望和有效的解决方案.
关键词:
云计算是一种云计算.网络安全 网络安全有效的网络有效的网络增强的足球队训练算法侵入检测入侵检测系统可以检测入侵者.这就是为什么物联网是物联网物联网.机器学习 机器学习这种算法是Metaheuristic算法.优化技术的优化技术

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  • 深度学习和元启发学的整合为先进的入侵检测提供了一个强大的框架.
  • 这些发现突出了拟议方法的潜力,可以显著提高连接系统的保护.