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相关概念视频

Leaky Scanning02:28

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During most eukaryotic translation processes, the small 40S ribosome subunit scans an mRNA from its 5' end until it encounters the first start AUG codon. The large 60S ribosomal subunit then joins the smaller one to initiate protein synthesis. The location of the translation initiation is largely determined by the nucleotides near the start codon as there may be multiple translation initiation sites present on the mRNA.  Marilyn Kozak discovered that the sequence RCCAUGG (where R...
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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...
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Although black holes were theoretically postulated in the 1920s, they remained outside the domain of observational astronomy until the 1970s.
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When one or more data points appear far from the rest of the data, there is a need to determine whether they are outliers and whether they should be eliminated from the data set to ensure an accurate representation of the measured value. In many cases, outliers arise from gross errors (or human errors) and do not accurately reflect the underlying phenomenon. In some cases, however, these apparent outliers reflect true phenomenological differences. In these cases, we can use statistical methods...
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Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. Consider a lifting tong carrying a 100 kg load. It comprises movable sections DAF and CBG linked together with member AB.
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相关实验视频

Updated: Jul 24, 2025

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images
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一种基于深度学习的硬件木马检测成本驱动的方法.

Chen Dong1, Yinan Yao1, Yi Xu1

  • 1College of Computer and Data Science, Fuzhou University, Fuzhou 350116, China.

Sensors (Basel, Switzerland)
|July 8, 2023
PubMed
概括
此摘要是机器生成的。

本研究介绍了MHTtext,这是一种用于检测集成电路中的硬件木马的深度学习模型. 它提供灵活的策略来平衡精度和计算成本,提高网络物理系统和Metaverse的安全性.

关键词:
计算消费的计算消费.深度学习是一种深度学习.门口层面的门口水平.硬件 特洛伊木马 硬件 特洛伊木马集成电路安全性 集成电路安全性语义分析 语义分析

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科学领域:

  • 计算机科学 计算机科学
  • 电气工程 电气工程
  • 网络安全 网络安全

背景情况:

  • 网络物理系统和Metaverse面临越来越多的硬件安全威胁,特别是集成电路中的硬件木马.
  • 现有的硬件木马检测方法因金色芯片和高计算需求等局限性而难以进行大规模集成.
  • 传统的机器学习方法用于硬件木马检测往往是不稳定的,因为手动特征提取的困难.

研究的目的:

  • 提出一种新的基于深度学习的多尺度检测模型,MHTtext,用于自动硬件木马特征提取和识别.
  • 在MHTtext中开发策略,以平衡实际应用的检测准确性和计算效率.
  • 引入一个新的评估指标,稳定效率指数 (SEI),用于评估模型的性能和稳定性.

主要方法:

  • MHTtext模型使用深度学习从网列数据中自动提取特征.
  • 实施了两种不同的策略 (全球和本地),以满足不同的准确性和计算要求.
  • 文本CNN用于硬件特洛伊木马识别,具有确保不重复组件信息的机制,以提高稳定性.

主要成果:

  • 在MHTtext的全球策略中,在基准网清单上检测硬件木马的平均准确率达到99.26%.
  • MHTtext模型表现出高度的稳定性和灵活性,其中一个策略在SEI中在比较分类器中排名第一.
  • 当地战略也取得了出色的结果,证明了该模型在不同操作模式中的有效性.

结论:

  • 拟议的MHTtext模型为大型集成电路中的硬件木马检测提供了一个稳定,灵活和准确的解决方案.
  • 双策略方法允许基于特定应用需求的可适应性性能,解决传统方法的局限性.
  • MHTtext有助于提高像Metaverse这样的不断发展的数字环境中的关键硬件组件的安全性.