Jove
Visualize
联系我们

相关实验视频

EnCTN:一个增强的人工智能支持的深度学习框架,用于增强区块链交易的安全性.

P Bhuvaneshwari1, A Krishnaveni2, Y Harold Robinson3

  • 1School of Computer Engineering, Manipal Institute of Technology Bengaluru, Manipal Academy of Higher Education, Manipal, India. bhuvaneshwari.p@manipal.edu.

Scientific reports
|November 27, 2025
PubMed
概括

相关概念视频

Issues And Trends In Healthcare Delivery System01:29

Issues And Trends In Healthcare Delivery System

6.1K
The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
6.1K
Non-equilibrium in the Cell01:16

Non-equilibrium in the Cell

5.3K
An important concept in studying metabolism and energy is that of chemical equilibrium. Most chemical reactions are reversible. They can proceed in both directions, releasing energy into their environment in one direction, and absorbing it from the environment in the other direction. The same is true for the chemical reactions involved in cell metabolism, such as the breaking down and building up of proteins into and from individual amino acids, respectively. Reactants within a closed system...
5.3K

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

IoMT-Blockchain framework for secure and real-time heart disease monitoring using hybrid black-winged optimized spherical structural graph convolutional neural networks.

Scientific reports·2026
Same author

Strengthening of structurally deficient and partially damaged short square columns using GFRECC retrofit technique.

Scientific reports·2025
Same author

BSVA: blockchain-enabled secured vertical aggregation algorithm for transactions management in drug traceability framework.

Scientific reports·2025
Same author

Three Dimensional Model Planning for Vector Determination in Alveolar Distraction Osteogenesis: A Technical Note.

Journal of maxillofacial and oral surgery·2024
Same author

IoT Based Smart Assist System to Monitor Entertainment Spots Occupancy and COVID 19 Screening During the Pandemic.

Wireless personal communications·2022
Same author

Banana Plant Disease Classification Using Hybrid Convolutional Neural Network.

Computational intelligence and neuroscience·2022
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

本研究介绍了一种支持深度学习的区块链框架,用于安全的数据管理. 这种新的方法提高了数据的耐用性和匿名性,提高了异常检测的准确性.

科学领域:

  • 人工智能的人工智能
  • 区块链技术 区块链技术
  • 数据安全 数据安全

背景情况:

  • 深度学习为基于人工智能 (AI) 的区块链框架提供先进的解决方案.
  • 确保区块链交易中的数据可靠性,保密性和匿名性至关重要.
  • 现有的方法需要改进,以获得可靠的数据耐用性和传播.

研究的目的:

  • 为增强数据耐用性和交易分析提出混合区块链和深度学习模型.
  • 开发一个安全的,支持深度学习的区块链交易模型,解决保密和匿名问题.
  • 改进区块链系统中的时间异常检测.

主要方法:

  • 使用一个增强的卷积时间网络 (EnCTN) 进行交易分析.
  • 采用了一个移动窗口提取技术,用于时间序列数据.
  • 包含扩展卷积来捕捉远程依赖关系.
  • 在以太坊使用Python实现了框架.

主要成果:

  • 拟议的技术在几个参数上表现出了比现有方法更好的性能.
  • 在NSL-KDD数据集上实现了增强的异常分类准确性.
  • 该框架有效地检测时间异常,提高了计算效率.
关键词:
异常检测检测异常检测自动编码器自动编码器区块链 区块链 区块链 区块链深度学习是一种深度学习.安全的安全的安全的安全的安全.智能交易是一种智能交易.时间卷积网络的时间卷积网络.

相关实验视频

结论:

  • 混合区块链和深度学习方法为现实世界的异常检测提供了有效的解决方案.
  • EnCTN模型显著提高了区块链系统中的数据耐用性和传播.
  • 该框架提供了时间异常的准确发现,并提高了计算效率.