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

What are Populations and Communities?00:30

What are Populations and Communities?

37.0K
Overview
37.0K
Censoring Survival Data01:09

Censoring Survival Data

516
Survival analysis is a statistical method used to analyze time-to-event data, often employed in fields such as medicine, engineering, and social sciences. One of the key challenges in survival analysis is dealing with incomplete data, a phenomenon known as "censoring." Censoring occurs when the event of interest (such as death, relapse, or system failure) has not occurred for some individuals by the end of the study period or is otherwise unobservable, and it might have many different...
516

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

GCSAM: Gradient Centralized Sharpness Aware Minimization.

IEEE access : practical innovations, open solutions·2025
Same author

Automated Skin Cancer Report Generation via a Knowledge-Distilled Vision-Language Model.

IEEE access : practical innovations, open solutions·2025
Same author

Comprehensive Toughness Dataset of Nuclear Reactor Structural Materials using Charpy V-Notch Impact Testing.

Scientific data·2025
Same author

Comparative Analysis of Multi-Omics Integration Using Graph Neural Networks for Cancer Classification.

IEEE access : practical innovations, open solutions·2025
Same author

Dataset of tensile properties for sub-sized specimens of nuclear structural materials.

Scientific data·2025
Same author

Machine Learning for Additive Manufacturing of Functionally Graded Materials.

Materials (Basel, Switzerland)·2024
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: Jan 13, 2026

Behavioral Tracking and Neuromast Imaging of Mexican Cavefish
14:58

Behavioral Tracking and Neuromast Imaging of Mexican Cavefish

Published on: April 6, 2019

8.2K

从捕获-回收到没有回收:即使在软件更新后也有效的SCAD.

Kurt A Vedros1, Aleksandar Vakanski1, Domenic J Forte2

  • 1University of Idaho, Moscow, ID 83844, USA.

Sensors (Basel, Switzerland)
|January 10, 2026
PubMed
概括
此摘要是机器生成的。

生成模型现在可以为更新的物联网设备软件创建现实的电磁信号,克服侧通道异常检测的主要障碍. 这一创新使得检测固件改变得更加有效和准确.

关键词:
检测异常检测异常检测生成性的对抗性网络.侧通道分析

更多相关视频

Methods for Image-based Surveys of Benthic Macroinvertebrates and Their Habitat Exemplified by the Drop Camera Survey for the Atlantic Sea Scallop
07:43

Methods for Image-based Surveys of Benthic Macroinvertebrates and Their Habitat Exemplified by the Drop Camera Survey for the Atlantic Sea Scallop

Published on: July 2, 2018

10.0K
Development of New Methods for Quantifying Fish Density Using Underwater Stereo-video Tools
09:32

Development of New Methods for Quantifying Fish Density Using Underwater Stereo-video Tools

Published on: November 20, 2017

9.7K

相关实验视频

Last Updated: Jan 13, 2026

Behavioral Tracking and Neuromast Imaging of Mexican Cavefish
14:58

Behavioral Tracking and Neuromast Imaging of Mexican Cavefish

Published on: April 6, 2019

8.2K
Methods for Image-based Surveys of Benthic Macroinvertebrates and Their Habitat Exemplified by the Drop Camera Survey for the Atlantic Sea Scallop
07:43

Methods for Image-based Surveys of Benthic Macroinvertebrates and Their Habitat Exemplified by the Drop Camera Survey for the Atlantic Sea Scallop

Published on: July 2, 2018

10.0K
Development of New Methods for Quantifying Fish Density Using Underwater Stereo-video Tools
09:32

Development of New Methods for Quantifying Fish Density Using Underwater Stereo-video Tools

Published on: November 20, 2017

9.7K

科学领域:

  • 网络安全 网络安全
  • 嵌入式系统 嵌入式系统
  • 信号处理 信号处理

背景情况:

  • 基于侧通道的异常检测 (SCAD) 使用物理信号,如电磁辐射,用于物联网/网络物理系统的完整性检查.
  • 目前的SCAD方法需要每次软件更新都需要昂贵的重新指纹,这阻碍了实际部署.
  • 物联网设备容易受到固件改和部署后妥协的影响.

研究的目的:

  • 为新的或更新的执行路径开发一个生成型建模框架,用于合成现实的电磁 (EM) 信号.
  • 为了解决SCAD系统中手动指纹采集的局限性.
  • 提高SCAD的效率和可扩展性,以适应不断变化的物联网环境.

主要方法:

  • 使用了有条件的瓦斯斯坦生成对抗网络与梯度惩罚 (CWGAN-GP) 框架.
  • 训练了CWGAN-GP在真正的EM轨迹上,条件是执行状态描述器 (ESD) 编码指令序列,操作数和注册值.
  • 在指令级别对真实EM排放的合成信号忠实度进行评估.

主要成果:

  • 生成的合成电磁信号与真实辐射达到85-92%的相似性.
  • 通过ESD调节,信号保真度提高了大约13%.
  • 在合成数据上训练的半监督探测器的性能与在真实数据上训练的探测器相似 (ROC-AUC在±1%以内).
  • 与ResGAN.com等先前方法相比,1DCNNGAN模型变体提供了更快的训练和更少的内存使用.

结论:

  • 提出的生成框架有效地合成了现实的EM信号,为更新的软件提供了高效的SCAD.
  • 这种方法大大降低了与SCAD系统中重新指纹处理相关的开销.
  • 该方法显示了加强物联网和网络物理系统的安全性和完整性监控的巨大潜力.