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在智能电网中以物联网为基础的基于雾的安全聚合,支持数据分析.

Hayat Mohammad Khan1, Farhana Jabeen1, Abid Khan2

  • 1Department of Computer Science, COMSATS University, Islamabad 45550, Pakistan.

Sensors (Basel, Switzerland)
|October 16, 2025
PubMed
概括
此摘要是机器生成的。

本研究介绍了智能电网的安全数据分析方案,提高了隐私和效率. 支持雾的安全数据分析操作 (FESDAO) 计划确保数据完整性和对攻击的弹性.

关键词:
这是一个ANOVA.BGN BGN BGN BGN BGN 在线有很多很多的东西.数据分析数据分析.有一个错误容忍度.雾计算 雾计算 雾计算同型型的加密方式.保护隐私 保护隐私 保护隐私智能电网是一个智能电网.统计分析是一种统计分析.

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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:

  • 物联网 (IoT) 提供了自动化和效率,智能电网从物联网和数据分析中受益,以改善能源管理.
  • 数据分析,特别是统计分析,对于从智能电网数据中提取见解至关重要,但隐私和安全是主要问题.
  • 当前的智能电网系统在安全汇总和分析数据方面面临着挑战,同时保持隐私和弹性.

研究的目的:

  • 为智能电网提出一个安全,保护隐私的数据聚合方案.
  • 通过分布式架构增强智能电网中的数据分析能力.
  • 解决安全漏洞,包括内部威胁,虚假数据注入和重复攻击.

主要方法:

  • 介绍了支持雾的安全数据分析操作 (FESDAO) 计划,一个分布式架构.
  • 实施修改后的Boneh-Goh-Nissim加密方案,用于保护隐私的数据聚合.
  • 集成安全的聚合,身份验证,容错和弹性机制.
  • 支持云和雾节点级别的统计分析.

主要成果:

  • FESDAO提供了强大的安全功能,包括安全聚合,身份验证和容错等.
  • 该方案确保数据在聚合期间的隐私,并支持准确的统计分析.
  • 费斯达奥证明了对内部威胁,虚假数据注入和重复攻击的弹性,即使计数器故障.
  • 绩效评估显示,FESDAO在各种成本方面,与现有计划相比,效率高.

结论:

  • 拟议的FESDAO计划有效地提高了智能电网数据分析中的安全性和隐私性.
  • 它为智能电网中的数据聚合和分析提供了可靠和有弹性的解决方案.
  • 费斯达奥在能源领域对物联网和数据分析的安全整合做出了重大贡献.