Research on FDI Attacks in Edge Computing Environment. (September 2020)

• Record Type: Journal Article
• Authors: Li, Qing; Xu, Aidong; Lin, Haojie; Hou, Wenjing; Jiang, Yixin; Zhang, Yunan; Mao, Zhongqi; Wen, Hong
• Is Part Of: Journal of physics. Volume 1646(2020)
• Publication Date: 2020-09
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1646/1/012013
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: The False Data Injection (FDI) attack in the smart grid can bypass the bad data detection mechanism and make the control center make an incorrect estimate of the system status. The smart grid under the edge computing architecture is more likely to be maliciously attacked by the terminal because it is close to the terminal. For this reason, this paper proposes a method combining PCA and ReliefF algorithm to achieve the purpose of dimensionality reduction. It can solve the overfitting problem caused by the high dimensionality of traditional machine learning attack signal detection, and it is suitable for terminals with low computing power.