34امین کنفرانس بین المللی برق , 2019-10-21

Title : ( Runtime Optimization of a New Anomaly Detection Method for Smart Metering Data Using Hadoop Map-Reduce )

Authors: Farid Fathnia , Mohammadreza Barazesh , Mohammad Hossein Javidi Dasht Bayaz ,

Citation: BibTeX | EndNote

Abstract

In this paper, we will try to speed up the identification of abnormalities and disturbances that are generated in the data sent from smart meters to the control center by cyber attackers. Two important points in this discussion are the high precision of the proposed method and the speed of its identification. High accuracy is a separate topic and has been documented by same authors in another article. The speed of the method should also be considered in order to prevent possible losses from the onset of a cyber-attack during the operation of the power grid. Therefore, by involving a new computing environment with the term \\\"Cloud Computing\\\", we try to speed up the detection. How to do this process and how to simulate the hardware and software of this topic will come through this article.

Keywords

, Anomaly Detection; Electricity Market; Smart Meter; Cloud Computing; Hadoop; Map, reduce
برای دانلود از شناسه و رمز عبور پرتال پویا استفاده کنید.

@inproceedings{paperid:1078456,
author = {Fathnia, Farid and Barazesh, Mohammadreza and Javidi Dasht Bayaz, Mohammad Hossein},
title = {Runtime Optimization of a New Anomaly Detection Method for Smart Metering Data Using Hadoop Map-Reduce},
booktitle = {34امین کنفرانس بین المللی برق},
year = {2019},
location = {تهران, IRAN},
keywords = {Anomaly Detection; Electricity Market; Smart Meter; Cloud Computing; Hadoop; Map-reduce},
}

[Download]

%0 Conference Proceedings
%T Runtime Optimization of a New Anomaly Detection Method for Smart Metering Data Using Hadoop Map-Reduce
%A Fathnia, Farid
%A Barazesh, Mohammadreza
%A Javidi Dasht Bayaz, Mohammad Hossein
%J 34امین کنفرانس بین المللی برق
%D 2019

[Download]