Open AccessAnalysis of Internal Threat Detection Methods of Power Grid under the Characteristic Cloud Computing Model
Author(s) -
Jing Li,
Jie Huang,
Fen Liu
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1852/2/022072
Subject(s) - cloud computing , grid , computer science , power grid , distributed computing , power (physics) , work (physics) , control (management) , grid computing , computer security , risk analysis (engineering) , industrial engineering , systems engineering , data science , business , engineering , artificial intelligence , operating system , mechanical engineering , physics , geometry , mathematics , quantum mechanics
Advances in science and technology are driving the development of society, and with the development of society, our power grid coverage has become more extensive, which has solved the power supply problem in most parts of the country. As an important infrastructure of the country, the safety and nursing work of the power grid industrial control system is very important. However, the increase of coverage makes the maintenance and management of the power grid itself more difficult, and the internal threat of the power grid can not be ignored. To get a clearer understanding of the methods and patterns we use in terms of threats within the grid, this article will analyze the objects we are studying us using cloud computing simulation methods, and then analyze the results of the data. The experimental results show that the detection method of internal threat of power grid is still in the preliminary stage of development in our country.