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相关概念视频

Leaky Scanning02:28

Leaky Scanning

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 stands for...
Detection of Black Holes01:10

Detection of Black Holes

Although black holes were theoretically postulated in the 1920s, they remained outside the domain of observational astronomy until the 1970s.
Their closest cousins are neutron stars, which are composed almost entirely of neutrons packed against each other, making them extremely dense. A neutron star has the same mass as the Sun but its diameter is only a few kilometers. Therefore, the escape velocity from their surface is close to the speed of light.
Not until the 1960s, when the first neutron...
Masking and Demasking Agents01:19

Masking and Demasking Agents

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 the metal...
Mass Analyzers: Overview01:13

Mass Analyzers: Overview

The mass analyzer is a crucial component of the mass spectrometer. In the ionization chamber, the vaporized sample is bombarded with a high-energy electron beam to generate a radical cation and further fragment into neutral molecules, radicals, and cations. A series of negatively charged accelerator plates accelerate the cations into the mass analyzer. The mass analyzer separates ions according to their mass-to-charge (m/z) ratios and then directs them to the detector. The common types of mass...
Introduction to Virus01:28

Introduction to Virus

Viruses are unique biological entities that blur the boundary between living and non-living systems. Although they lack cellular structure and metabolic processes, they can exhibit characteristics of life when infecting a host. Their defining feature is a nucleic acid core, composed of either DNA or RNA, encapsulated within a protein coat called a capsid. This simple structure allows them to invade host cells and use their machinery for replication efficiently.Viral Structure and...
Viruses with RNA Genomes01:29

Viruses with RNA Genomes

RNA viruses are categorized into positive-strand, negative-strand, or double-stranded groups based on their genomic structure and replication mechanisms. This classification dictates how they exploit host cellular machinery for protein synthesis and replication. Some RNA viruses also utilize reverse transcription as part of their life cycle, further diversifying their replication strategies.Positive-Strand RNA VirusesPositive-strand RNA viruses have genomes that function directly as messenger...

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相关实验视频

Updated: May 12, 2026

Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment
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Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment

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基于BERT组合的MBR框架用于安卓恶意软件检测.

Faisal S Alsubaei1, Abdulwahab Ali Almazroi2, Walid Said Atwa2,3

  • 1Department of Cybersecurity, College of Computer Science and Engineering, University of Jeddah, Jeddah, 21959, Saudi Arabia. fsalsubaei@uj.edu.sa.

Scientific reports
|April 24, 2025
PubMed
概括
此摘要是机器生成的。

本研究介绍了一种新的BERT Ensemble (MBR) 框架,用于在物联网设备中检测Android恶意软件. MBR模型实现了高精度,为增强系统安全性和用户隐私提供了可靠的解决方案.

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Effective Analysis of Human Exposure Conditions with Body-worn Dosimeters in the 2.4 GHz Band
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Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
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科学领域:

  • 网络安全 网络安全
  • 机器学习 机器学习
  • 物联网 (IoT) 的物联网 (IoT) 的物联网.

背景情况:

  • 安卓恶意软件对物联网设备构成重大风险.
  • 现有的Android恶意软件检测方法在复杂的物联网环境中面临挑战.

研究的目的:

  • 在基于推系统的物联网中开发一种用于Android恶意软件检测 (AMD) 的新框架.
  • 为了增强系统安全和用户隐私,对抗不断发展的Android恶意软件威胁.

主要方法:

  • 开发了一个与MobileNetV2结合的BERT Ensemble (MBR) 模型.
  • 使用100个Android应用程序权限和精细的功能集的子集进行威胁分析技术.
  • 集成方法应用于用于恶意软件检测的静态数据.

主要成果:

  • MBR模型实现了98%的准确性,96%的精度,98%的回忆率和97%的F1得分.
  • 与MCADS,DroidRL,CNN,FAGnet,GAN和FEDriod相比,该框架表现出更高的性能.
  • 记录了0.058的低日志损失,表明模型可靠性很高.

结论:

  • MBR框架为物联网中的Android恶意软件检测提供了可靠和创新的解决方案.
  • 该研究解决了面对越来越多的Android恶意软件风险的关键用户隐私和系统安全问题.
  • 这项研究提出了一种新的策略,用于恶意软件检测,使用对静态数据的集合方法.