Research and Application of Terminal Vulnerability Mining System of Electric Power Company Based on Artificial Intelligence

EasyChair Preprint 6661

Abstract

In the era of Energy Internet, prefecture and municipal power supply companies are faced with a large number of underlying terminal equipment. Traditional manual detection of vulnerabilities has the disadvantages of low batch processing efficiency and unstable vulnerability detection rate. This article combines vulnerability mining and artificial intelligence, using bidirectional LSTM network. Feature learning is used as the core algorithm of the automatic vulnerability mining module, and has been applied in practice in the world-class urban power distribution network demonstration project in the ancient city of Suzhou. The application results show that the terminal vulnerability mining system based on artificial intelligence can greatly improve the automatic discovery ability and analysis efficiency of terminal equipment high-risk vulnerabilities, and can effectively improve the defects of traditional methods that cannot be batched and modularized.

Keyphrases: Artificial Intelligence, Bidirectional LSTM, Energy Internet, Vulnerability Mining

@booklet{EasyChair:6661,
  author    = {Gu Yangqing and Yang Yu and Li Heting},
  title     = {Research and Application of Terminal Vulnerability Mining System of Electric Power Company Based on Artificial Intelligence},
  howpublished = {EasyChair Preprint 6661},
  year      = {EasyChair, 2021}}