Intrusion detection system using Online Sequence Extreme Learning Machine (OS-ELM) in advanced metering infrastructure of smart grid.

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ID: 128223
2018
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Abstract
Advanced Metering Infrastructure (AMI) realizes a two-way communication of electricity data through by interconnecting with a computer network as the core component of the smart grid. Meanwhile, it brings many new security threats and the traditional intrusion detection method can't satisfy the security requirements of AMI. In this paper, an intrusion detection system based on Online Sequence Extreme Learning Machine (OS-ELM) is established, which is used to detecting the attack in AMI and carrying out the comparative analysis with other algorithms. Simulation results show that, compared with other intrusion detection methods, intrusion detection method based on OS-ELM is more superior in detection speed and accuracy.
Reference Key
li2018intrusionplos Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Li, Yuancheng;Qiu, Rixuan;Jing, Sitong;
Journal PloS one
Year 2018
DOI
10.1371/journal.pone.0192216
URL
Keywords
internet of things (iot) security game theory iterated public goods game (ipgg) zero-determinant strategy

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