Visible to the public The Security Evaluation of Big Data Research for Smart Grid

TitleThe Security Evaluation of Big Data Research for Smart Grid
Publication TypeConference Paper
Year of Publication2019
AuthorsLi, Zhifeng, Li, Yintao, Lin, Peng
Conference Name2019 15th International Wireless Communications Mobile Computing Conference (IWCMC)
Date Publishedjun
KeywordsBig Data, Big Data analytics, Big Data method, Big Data research, big data security metrics, big data technologies, Classification algorithms, Data analysis, machine learning, Metrics, power engineering computing, power system security, privacy, pubcrawl, reliability, Resiliency, Scalability, security, smart grid attacks, smart grid security, smart grid system, Smart grids, smart power grids, technological development
Abstract

The technological development of the energy sector also produced complex data. In this study, the relationship between smart grid and big data approaches have been investigated. After analyzing which areas of the smart grid system use big data technologies and technologies, big data technologies for detecting smart grid attacks have received attention. Big data analytics can produce efficient solutions and it is especially important to choose which algorithms and metrics to use. For this reason, an application prototype has been proposed that uses a big data method to detect attacks on the smart grid. The algorithm with high accuracy was determined to be 92% for random forests and 87% for decision trees.

DOI10.1109/IWCMC.2019.8766348
Citation Keyli_security_2019