The Security Evaluation of Big Data Research for Smart Grid
Title | The Security Evaluation of Big Data Research for Smart Grid |
Publication Type | Conference Paper |
Year of Publication | 2019 |
Authors | Li, Zhifeng, Li, Yintao, Lin, Peng |
Conference Name | 2019 15th International Wireless Communications Mobile Computing Conference (IWCMC) |
Date Published | jun |
Keywords | Big 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. |
DOI | 10.1109/IWCMC.2019.8766348 |
Citation Key | li_security_2019 |
- privacy
- technological development
- smart power grids
- Smart Grids
- smart grid system
- smart grid security
- smart grid attacks
- security
- Scalability
- Resiliency
- Reliability
- pubcrawl
- big data security metrics
- power system security
- power engineering computing
- Metrics
- machine learning
- data analysis
- Classification algorithms
- big data technologies
- Big Data research
- Big Data method
- Big Data Analytics
- Big Data