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

Neural Regulation01:37

Neural Regulation

Digestion begins with a cephalic phase that prepares the digestive system to receive food. When our brain processes visual or olfactory information about food, it triggers impulses in the cranial nerves innervating the salivary glands and stomach to prepare for food.
Neural Circuits01:25

Neural Circuits

Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
Neuronal pools are collections of nerve cells with similar functions and interact through chemical and electrical signals. These pools include both interneurons (the central neural circuit nodes that...
Neurons as Communicators of the Brain01:22

Neurons as Communicators of the Brain

Neurons, the fundamental units of the brain and nervous system, function as the primary transmitters of information throughout the body. Their ability to communicate through electrical and chemical signals is vital for every bodily function, from regulating the heartbeat to processing complex thoughts. Each neuron has three main components: the cell body (soma), dendrites, and an axon, each specialized to facilitate swift and efficient neural communication.
Cell Body
The cell body, also known...

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

Privacy-preserving verification of preprocessing in federated learning for genomic data.

JAMIA open·2026
Same author

Sustainable Personalized Home Care for Pandemic Management: A Service-Oriented Approach.

Digital government (New York, N.Y.)·2026
Same author

Semantically Correct Policy Mining and Enforcement for Attribute based Access Control.

ACM transactions on Internet technology·2026
Same author

Performance Analysis of Dynamic ABAC Systems using a Queuing Theoretic Framework.

Computers & security·2026
Same author

Privacy-Preserving Verification of ML Preprocessing via Model Behavior Indicators.

IEEE transactions on privacy·2026
Same authorSame journal

MALITE: Lightweight Malware Detection and Classification for Constrained Devices.

IEEE transactions on emerging topics in computing·2025

相关实验视频

Updated: May 12, 2026

Revealing Neural Circuit Topography in Multi-Color
09:11

Revealing Neural Circuit Topography in Multi-Color

Published on: November 14, 2011

14.9K

神经网络的雕刻,秘密和可解释性

Nathaniel Hobbs1, Periklis A Papakonstantinou1, Jaideep Vaidya1

  • 1Rutgers University, NJ.

IEEE transactions on emerging topics in computing
|April 21, 2025
PubMed
概括

本研究介绍了将信息秘密嵌入神经网络 (NN) 的方法. 一些方法是脆弱的,但更系统的方法抵抗检测和攻击,确保NN安全.

科学领域:

  • 计算机科学 计算机科学
  • 人工智能的人工智能
  • 机器学习 机器学习

背景情况:

  • 神经网络 (NN) 在社会中变得越来越重要.
  • 确保 NN 培训和使用的完整性至关重要.
  • 在NN中嵌入不可检测信息的问题需要进行系统的调查.

研究的目的:

  • 在NNs.NN.中刻出秘密信息的安全标准.
  • 开发机器学习方法,用于创建雕刻的NN.
  • 建立一个威胁模型,用可解释性方法来评估刻画安全性.

主要方法:

  • 机器学习训练算法用于构建雕刻的NNs.
  • 基于定义的威胁模型开发区分算法.
  • 在图像分类数据集上对最先进的解释性方法进行雕刻弹性评估.

主要成果:

  • 关于在NNs中对秘密刻画的安全性提出的定义.
  • 演示了用于雕刻网络的机器学习结构.
  • 确定了对拟议的区分器脆弱的特定的NN雕刻.
  • 展示了系统雕刻对对基准数据集的区分攻击的弹性.
关键词:
后门攻击后门攻击数据中毒数据中毒雕刻 雕刻 雕刻 雕刻可以解释的解释性.机器学习是机器学习.神经网络的神经网络安全的安全的安全的安全的安全.

更多相关视频

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
11:18

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Published on: March 2, 2015

10.2K
Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

901

相关实验视频

Last Updated: May 12, 2026

Revealing Neural Circuit Topography in Multi-Color
09:11

Revealing Neural Circuit Topography in Multi-Color

Published on: November 14, 2011

14.9K
Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
11:18

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Published on: March 2, 2015

10.2K
Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

901

结论:

  • 开发的威胁模型为NN解释性方法提供了一个基准.
  • 系统的雕刻方法提供了抵御检测和攻击的弹性.
  • 这项工作促进了神经网络的安全性和可信度.