Jove
Visualize
联系我们

相关概念视频

Masking and Demasking Agents01:19

Masking and Demasking Agents

3.4K
EDTA titrations may necessitate masking and demasking agents to temporarily protect a particular metal ion in a mixture from the EDTA reaction. These agents facilitate the sequential analysis of the metal ions by forming stable complexes with some—but not all—metal ions during certain steps.
There are many masking agents, such as cyanide, fluoride, triethanolamine, thiourea, and 2,3-bis(sulfanyl)propan-1-ol (formerly 2,3-dimercapto-1-propanol), with the masking agent chosen based on...
3.4K
Improving Translational Accuracy02:07

Improving Translational Accuracy

3.6K
3.6K
Improving Translational Accuracy02:07

Improving Translational Accuracy

14.1K
Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
14.1K
Associative Learning01:27

Associative Learning

1.3K
Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
Classical conditioning, also known...
1.3K

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

OptoRibo-seq for spatiotemporally resolved mapping of the local protein translatome.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same author

Microsurgery of a rare case of abducens schwannoma: surgical techniques.

Chinese clinical oncology·2026
Same author

Recurrent CIC-rearranged sarcoma of central nervous system: a clinicopathological case report.

Frontiers in oncology·2026
Same author

DHX9 sustains hematopoietic stem cell function in cooperation with H3 acetylation.

Stem cell reports·2026
Same author

MFSD-YOLO: A multi-scale feature detection network for pediatric wrist abnormalities in radiographic images.

PloS one·2026
Same author

Efficient Privacy-Preserving Face Recognition Based on Feature Encoding and Symmetric Homomorphic Encryption.

Entropy (Basel, Switzerland)·2026
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

相关实验视频

Updated: Jan 17, 2026

Generating Strictly Controlled Stimuli for Figure Recognition Experiments
05:39

Generating Strictly Controlled Stimuli for Figure Recognition Experiments

Published on: March 18, 2019

5.5K

休眠钥匙:解锁文本到图像模型中的通用对抗控制.

Jingqi Hu1, Li Li1, Hanzhou Wu1

  • 1School of Communication and Information Engineering, Shanghai University, Shanghai, 200444, China.

Neural networks : the official journal of the International Neural Network Society
|September 13, 2025
PubMed
概括

一个新的通用对抗性攻击,休眠密钥,绕过了文本到图像 (T2I) 模型中的安全过器. 这个插件后有效地在各种提示中产生误导性或不安全的工作内容 (NSFW).

科学领域:

  • 人工智能的人工智能
  • 计算机视觉 计算机视觉
  • 网络安全 网络安全

背景情况:

  • 文本到图像 (T2I) 扩散模型在图像生成方面表现出色,但存在安全风险.
  • 恶意提示程序修改可以绕过安全过器,产生误导性或不安全的工作 (NSFW) 内容.
  • 现有的对抗性攻击缺乏通用性,并且可以通过当前的防御来检测.

研究的目的:

  • 为T2I传播模型提出一个通用的对抗性攻击框架.
  • 开发一种方法,绕过现有的安全机制,提高攻击的可转移性和不可感知性.
  • 为了解决提示符特定攻击和可检测的文本空间干扰的局限性.

主要方法:

  • 引入了"休眠密钥",一个通用的对抗性攻击框架.
  • 开发了一个可转移的后,作为任何文本输入的插件.
  • 实施了层次梯度聚合策略,以在各种提示中进行强大的优化.

主要成果:

  • "休眠密钥"框架展示了攻击性能和隐形之间有效的平衡.
  • 与基线相比,NSFW生成任务的成功率提高了18%.
  • 成功绕过主要的安全机制,包括关键字过,语义分析和文本分类器.
关键词:
敌对的攻击是敌对的攻击.模型的坚固性 模型的坚固性文本到图像模型模型全球性扰动 普遍扰动

相关实验视频

Last Updated: Jan 17, 2026

Generating Strictly Controlled Stimuli for Figure Recognition Experiments
05:39

Generating Strictly Controlled Stimuli for Figure Recognition Experiments

Published on: March 18, 2019

5.5K

结论:

  • 拟议的"休眠密钥"框架为T2I模型提供了强大的和可转移的对抗性攻击.
  • 这种方法增强了与T2I传播模型相关的安全风险,特别是对于NSFW内容生成.
  • 这些发现凸显了对AI图像生成中对复杂的对抗性攻击进行先进防御机制的需求.