区块链和机器学习启发了安全的智能家居通信网络
Subhita Menon1, Divya Anand1, Kavita2
1School of Computer Science and Engineering, Lovely Professional University, Phagwara 144411, India.
Sensors (Basel, Switzerland)
|July 14, 2023
概括
本研究介绍了使用区块链和云数据评估的智能家居网络的安全学习引擎. 它提高了安全性和效率,优于现有的AI-IoT技术,为更好的用户生活方式提供了更好的性能.
科学领域:
- 计算机科学 计算机科学
- 网络安全 网络安全
- 人工智能的人工智能
背景情况:
- 通过物联网 (IoT) 互联的智能家居设备的扩散带来了重大的安全挑战.
- 现有的安全措施很难有效地管理智能家居网络中复杂的数据流和潜在威胁.
研究的目的:
- 为智能家居通信网络提出一种新的学习引擎,该引擎集成区块链和基于云的数据评估.
- 提高智能家居通信系统的安全性,效率和决策能力.
主要方法:
- 实现一个区块链层,用于安全的用户身份验证和网络分类账生成.
- 利用基于云的数据评估层将智能家居数据分类为智能交易 (T),修改交易 (T) 和避免交易 (T).
- 采用神经网络进行训练和分类,以改善区块链层的决策.
主要成果:
- 与融合实时序列深度极端学习机器 (RTS-DELM),数据融合技术和AI-IoT技术相比,拟的学习引擎表现出卓越的性能.
- 实现了较低的平均计算复杂性和较低的虚假身份验证率.
- 提供了增强的电子信息工程和优化方案.
结论:
- 开发的系统确保了安全高效的智能家居通信网络.
- 区块链和人工智能驱动的数据分析的整合显著改善了网络安全和性能.
- 改进后的系统通过安全高效的智能家居技术,有助于改善整体生活方式.
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