Research Article
Mining Network Security Holes Based on Data Flow Analysis in Smart Grid
@INPROCEEDINGS{10.1007/978-3-030-49610-4_5, author={Yang Li and Xiaohua Liu and Lixin Zhang and Wenbin Guo and Qian Guo}, title={Mining Network Security Holes Based on Data Flow Analysis in Smart Grid}, proceedings={Smart Grid and Internet of Things. Third EAI International Conference, SGIoT 2019, TaiChung, Taiwan, December 5-6, 2019, Proceedings}, proceedings_a={SGIOT}, year={2020}, month={6}, keywords={Big data Data analysis Vulnerability detection Smart grid}, doi={10.1007/978-3-030-49610-4_5} }- Yang Li
Xiaohua Liu
Lixin Zhang
Wenbin Guo
Qian Guo
Year: 2020
Mining Network Security Holes Based on Data Flow Analysis in Smart Grid
SGIOT
Springer
DOI: 10.1007/978-3-030-49610-4_5
Abstract
With the popularity of mobile terminals and the sharp increase in network data traffic, the problem of security loopholes has become increasingly prominent. The traditional vulnerability detection methods can no longer meet the demands for detection efficiency. In order to satisfy the high requirements on network security in the era of big data, the vulnerability mining technology is extremely urgent. This paper describes the current situation and introduces relevant security technology and algorithm in smart grid. The decision tree algorithm is selected as the basic algorithm of big data security technology. Through the test, the missing alarm rate and false alarm rate are simulated experimentally. We obtain the results of experiments by controlling variables, which proves that our algorithm can effectively detect IP scanning, Port scanning and other attacks.
