Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

A Chemical-Potential-Driven Self-Mitigation Mechanism during Calendar Aging.

Nano letters·2026
Same author

The Efficacy of Three Combinatory Decontamination Protocols and BMP-2-Incorporated BioCaP-Based Regenerative Material in Treating Implants With Peri-Implantitis In Vivo.

Clinical oral implants research·2026
Same author

Efficient Training of Large Vision Models via Advanced Automated Progressive Learning.

IEEE transactions on pattern analysis and machine intelligence·2026
Same author

Elevation from Binary to Ternary Resistive Switching Behaviors in Cubane-like Copper Iodide Clusters by Ligand Engineering.

Inorganic chemistry·2026
Same author

Ultrafast Multilevel Switching and Synaptic Behavior in a Planar Quantum Topological Memristor.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026
Same author

NiCd/ZnO nanocomposites: novel materials for photocatalytic degradation of Allura Red dye.

Scientific reports·2026
Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026
Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026
Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026
Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026
Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026
Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

Sensors (Basel, Switzerland)·2026
查看所有相关文章

相关实验视频

Updated: Jul 23, 2025

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

6.9K

使用机器学习有效检测网络攻击的多层过框架.

Muhammad Arsalan Paracha1, Muhammad Sadiq2, Junwei Liang2

  • 1Critical Infrastructure Protection and Malware Analysis Lab, Department of Computer and Information Sciences, Pakistan Institute of Engineering and Applied Sciences, Islamabad 44000, Pakistan.

Sensors (Basel, Switzerland)
|July 14, 2023
PubMed
概括
此摘要是机器生成的。

本研究引入了多层过框架 (MLFF),以减少入侵检测系统 (IDS) 中的检测时间,而不会牺牲准确性. MLFF提高了网络安全的机器学习模型的效率.

关键词:
在CIC-IDS2017中,我们将在2017年检测异常检测异常检测侵入检测系统的入侵检测系统机器学习是机器学习.网络攻击网络攻击.网络安全 网络安全安全信息和事件管理事件管理.

更多相关视频

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images
08:20

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images

Published on: October 27, 2023

1.5K
Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

581

相关实验视频

Last Updated: Jul 23, 2025

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

6.9K
Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images
08:20

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images

Published on: October 27, 2023

1.5K
Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

581

科学领域:

  • 计算机科学 计算机科学
  • 网络安全 网络安全
  • 机器学习 机器学习

背景情况:

  • 由于数字数据和互联网连接的增加,信息安全至关重要.
  • 侵入检测系统 (IDS) 对于保护网络免受攻击至关重要.
  • 现有的基于异常的IDS (艾滋病) 的研究往往忽视了检测时间效率.

研究的目的:

  • 提出一个多层过框架 (MLFF) 用于IDS的特征减少.
  • 通过最小化检测时间来提高入侵检测系统的效率.
  • 评估特征减少对IDS准确性和速度的影响.

主要方法:

  • 开发了一种连续的,三过多层过框架 (MLFF),使用统计方法来减少特征.
  • 使用CIC-IDS2017数据集进行实验验证.
  • 使用准确度,精度,回忆,F1得分,训练时间和检测时间来评估性能.

主要成果:

  • MLFF有效地减少了特征集,从而减少了检测时间.
  • 精确度,精度,回忆和F1分数在特征减少后仍然具有竞争力.
  • 决策树,随机森林和人工神经网络模型在最小的检测时间下表现出卓越的性能.

结论:

  • 拟议的MLFF是通过减少检测时间来优化IDS性能的有效策略.
  • 通过统计方法减少特征可以显著提高IDS的效率,而不会影响检测准确度.
  • 该框架为开发更快,更有效的网络安全解决方案提供了一种有价值的方法.