ETD-ConvLSTM: A Deep Learning Approach for Electricity Theft Detection in Smart Grids-Reference-Cited by-同舟云学术

ETD-ConvLSTM: A Deep Learning Approach for Electricity Theft Detection in Smart Grids

Published:2023 Issue: Volume:18 Page:2553-2568
ISSN:1556-6013
Container-title:IEEE Transactions on Information Forensics and Security
language:
Short-container-title:IEEE Trans.Inform.Forensic Secur.

Author:

Xia Xiaofang¹^ORCID,Lin Jian¹,Jia Qiannan¹,Wang Xiaoluan¹,Ma Chaofan²^ORCID,Cui Jiangtao¹^ORCID,Liang Wei³^ORCID

Affiliation:

1. School of Computer Science and Technology, Xidian University, Xi’an, China

2. Software College, Zhongyuan University of Technology, Zhengzhou, China

3. State Key Laboratory of Robotics, the Key Laboratory of Networked Control System, and the Institutes for Robotics and Intelligent Manufacturing, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China

Funder

Special Fund for Strategic Pilot Technology of Chinese Academy of Sciences

National Key Research and Development Program of China

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Safety, Risk, Reliability and Quality

Link

http://xplorestaging.ieee.org/ielx7/10206/9970396/10104583.pdf?arnumber=10104583

Reference35 articles.

1. Privacy-Preserving Energy Theft Detection in Smart Grids: A P2P Computing Approach

2. Energy Theft Detection in Multi-Tenant Data Centers with Digital Protective Relay Deployment

3. A Control Chart based Detector for Small-amount Electricity Theft (SET) Attack in Smart Grids

Cited by 15 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Kalman reinforcement learning-based provably secured smart grid false data intrusion detection and resilience enhancement;Electrical Engineering;2024-08-25

2. Deep fuzzy nets approach for energy efficiency optimization in smart grids;Applied Soft Computing;2024-08

3. Can Gas Consumption Data Improve the Performance of Electricity Theft Detection?;IEEE Transactions on Industrial Informatics;2024-06

4. Deep Anomaly Detection Framework Utilizing Federated Learning for Electricity Theft Zero-Day Cyberattacks;Sensors;2024-05-20

5. The Role of Deep Learning in Advancing Proactive Cybersecurity Measures for Smart Grid Networks: A Survey;IEEE Internet of Things Journal;2024-05-01