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Edge computing enabled non-technical loss fraud detection for big data security analytic in Smart Grid

机译:边缘计算可实现非技术损失欺诈检测,以实现智能电网中的大数据安全分析

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摘要

With the fast development of Smart Grid globally, the security issues arise sharply and Non-Technical Loss (NTL) fraud is one of the major security issues. There are some existing NTL fraud detectors, however, when big data security challenges emerge in Smart Grid, none of them can detect NTL fraud for big data in Smart Grid. In this paper, we propose ENFD, an NTL detection scheme enabled by Edge Computing and big data analytic tools to address big data NTL fraud detection problem in Smart Grid. The research work provides us with experience of developing big data security solutions in Smart Grid. The experimental results show that ENFD can efficiently detect big data NTL frauds which cannot be detected by the state-of-the-art detectors. ENFD can detect small data NTL frauds as well and the average detection speed is about six to seven times that of the fastest detector exists in the literature.
机译:随着全球智能电网的快速发展,安全问题急剧增加,非技术损失(NTL)欺诈是主要的安全问题之一。现有一些NTL欺诈检测器,但是,当智能电网中出现大数据安全挑战时,它们都无法检测到智能电网中大数据的NTL欺诈。在本文中,我们提出了ENFD,一种由Edge Computing和大数据分析工具支持的NTL检测方案,用于解决智​​能电网中的大数据NTL欺诈检测问题。这项研究工作为我们提供了在智能电网中开发大数据安全解决方案的经验。实验结果表明,ENFD可以有效地检测大数据NTL欺诈,而这是最新检测器无法检测到的。 ENFD还可以检测到小数据NTL欺诈,平均检测速度约为文献中最快检测器的六至七倍。

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