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A Fog-based Approach to Secure Smart Grids Against Data Integrity Attacks

机译:一种基于雾的方法来保护智能电网免受数据完整性攻击

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In this paper, a fog (edge) computing-based platform is proposed to realize distributed (localized) anomaly detection of data integrity attacks in smart grid applications aiming at addressing security and data privacy issues. To detect false data injection attacks, a distributed maximum likelihood (ML) estimator is implemented on the proposed fog-based platform. A series of simulation experiments are carried out to demonstrate the viability and efficacy of the proposed platform and, more importantly, of the distributed attack detection approach. The reported results, although preliminary in nature, move us a step closer to deploying fog computing technology in smart grid applications and in particular to further improving cyber-security of power networks.
机译:本文提出了一种基于雾(边缘)计算的平台,旨在解决智能电网应用中数据完整性攻击的分布式(局部)异常检测,旨在解决安全性和数据隐私问题。为了检测错误的数据注入攻击,在建议的基于雾的平台上实现了分布式最大似然(ML)估计器。进行了一系列仿真实验,以证明所提出平台的可行性和有效性,更重要的是,还证明了分布式攻击检测方法的可行性和有效性。报告的结果虽然本质上是初步的,但使我们离将雾计算技术部署到智能电网应用程序更近了一步,尤其是进一步提高了电力网络的网络安全性。

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