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

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

Schisandrin A suppresses hepatocellular carcinoma and sensitizes to sorafenib via modulating retinol metabolism.

American journal of cancer research·2026
Same author

OSBPL10 Drives Lipophagy-Mediated Lipid Mobilization to Promote Pancreatic Ductal Adenocarcinoma Progression.

International journal of biological sciences·2026
Same author

LKCAFormer: a lightweight transformer with large-kernel cooperative attention for the segmentation of field maize leaf diseases.

BMC plant biology·2026
Same author

ENet-CAEM: a field strawberry disease identification model based on improved EfficientNetB0 and multiscale attention mechanism.

Frontiers in plant science·2025
Same author

LDL-MobileNetV3S: an enhanced lightweight MobileNetV3-small model for potato leaf disease diagnosis through multi-module fusion.

Frontiers in plant science·2025
Same author

Detection and Continuous Tracking of Breeding Pigs with Ear Tag Loss: A Dual-View Synergistic Method.

Animals : an open access journal from MDPI·2025
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: Jun 11, 2025

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images
08:20

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images

Published on: October 27, 2023

1.4K

基于改进的斑马优化算法和轻GBM的Android恶意软件的新型多分类动态检测模型.

Shuncheng Zhou1, Honghui Li1, Xueliang Fu1

  • 1College of Computer and Information Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China.

Sensors (Basel, Switzerland)
|September 28, 2024
PubMed
概括
此摘要是机器生成的。

这项研究引入了Android恶意软件的新动态检测模型IZOA-LightGBM,该模型显著提高了检测准确度. 该模型通过使用增强的优化算法优化机器学习超参数,有效地识别复杂的恶意软件.

关键词:
安卓恶意软件检测检测 安卓恶意软件检测轻GBMM 轻GBMM 的时间超参数优化超参数优化改进了斑马优化算法.

更多相关视频

Author Spotlight: A Smartphone-Based Imaging Method for C. elegans Lawn Avoidance Assay
07:39

Author Spotlight: A Smartphone-Based Imaging Method for C. elegans Lawn Avoidance Assay

Published on: February 24, 2023

9.8K
Comparative Analysis of Experimental Methods to Quantify Animal Activity in Caenorhabditis elegans Models of Mitochondrial Disease
05:51

Comparative Analysis of Experimental Methods to Quantify Animal Activity in Caenorhabditis elegans Models of Mitochondrial Disease

Published on: April 4, 2021

2.7K

相关实验视频

Last Updated: Jun 11, 2025

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images
08:20

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images

Published on: October 27, 2023

1.4K
Author Spotlight: A Smartphone-Based Imaging Method for C. elegans Lawn Avoidance Assay
07:39

Author Spotlight: A Smartphone-Based Imaging Method for C. elegans Lawn Avoidance Assay

Published on: February 24, 2023

9.8K
Comparative Analysis of Experimental Methods to Quantify Animal Activity in Caenorhabditis elegans Models of Mitochondrial Disease
05:51

Comparative Analysis of Experimental Methods to Quantify Animal Activity in Caenorhabditis elegans Models of Mitochondrial Disease

Published on: April 4, 2021

2.7K

科学领域:

  • 网络安全 网络安全
  • 机器学习 机器学习
  • 移动安全 移动安全

背景情况:

  • 安卓恶意软件正在迅速增加,对智能手机用户构成重大威胁.
  • 目前的静态分析方法与恶意软件所使用的复杂的模糊化技术作斗争.
  • 需要更有效,更准确的Android恶意软件检测方法.

研究的目的:

  • 为Android恶意软件提出一个新的动态检测模型.
  • 为了提高安卓恶意软件检测的准确性和效率.
  • 解决静态分析在检测模糊恶意软件方面的局限性.

主要方法:

  • 开发了一种改进的斑马优化算法 (IZOA),具有精英的基于对立的学习和火虫扰动.
  • 利用IZOA优化光梯度增强机 (LightGBM) 模型的超参数.
  • 实现了一个动态检测模型,IZOA-LightGBM,用于安卓恶意软件的多重分类.

主要成果:

  • 该IZOA-LightGBM模型实现了高检测准确度:在CICMalDroid-2020上达到了99.75%,在CCCS-CIC-AndMal-2020上达到了98.86%,在CIC-AAGM-2017上达到了97.95%.
  • 与其他现有模型相比,拟议的模型表现出优越的性能.
  • 优化算法的增强的融合速度和搜索能力.

结论:

  • 该IZOA-LightGBM模型为动态Android恶意软件检测提供了一个高度有效的解决方案.
  • 整合IZOA和LightGBM显著提高了对复杂恶意软件的检测准确度.
  • 这种方法提供了强大的防御,以抵御Android恶意软件日益增长的威胁.