Detection of False Data Injection Attacks in Smart Grid: A Secure
Federated Deep Learning Approach

Detection of False Data Injection Attacks in Smart Grid: A Secure Federated Deep Learning Approach

2 September 2022

Yang Li

M. Shahidehpour

Papers citing "Detection of False Data Injection Attacks in Smart Grid: A Secure Federated Deep Learning Approach"

8 / 8 papers shown

Title
Residual-Evasive Attacks on ADMM in Distributed Optimization Sabrina Bruckmeier Huadong Mo James Qin AAML 18 0 0 22 Apr 2025
Decentralized Federated Anomaly Detection in Smart Grids: A P2P Gossip Approach Muhammad Akbar Husnoo Adnan Anwar Md Enamul Haque A. N. Mahmood 42 1 0 10 Jan 2025
False Data Injection Attacks in Smart Grids: State of the Art and Way Forward Muhammad Irfan Alireza Sadighian Adeen Tanveer Shaikha J. Al‐Naimi Gabriele Oligeri 21 8 0 20 Aug 2023
Multi-Microgrid Collaborative Optimization Scheduling Using an Improved Multi-Agent Soft Actor-Critic Algorithm Jiankai Gao Yang Li Bin Wang Haibo Wu 16 11 0 01 Apr 2023
Optimal scheduling of island integrated energy systems considering multi-uncertainties and hydrothermal simultaneous transmission: A deep reinforcement learning approach Yang Li Fanjin Bu Yuanzheng Li Chao Long 11 87 0 27 Dec 2022
Wind Power Forecasting Considering Data Privacy Protection: A Federated Deep Reinforcement Learning Approach Yang Li Ruinong Wang Yuanzheng Li Meng Zhang Chao Long 18 176 0 02 Nov 2022
Privacy-preserving Spatiotemporal Scenario Generation of Renewable Energies: A Federated Deep Generative Learning Approach Yang Li Jiazheng Li Yi Wang 29 151 0 16 Jul 2021
Deep Learning for Intelligent Demand Response and Smart Grids: A Comprehensive Survey Praveen Kumar Viet Quoc Pham Madhusanka Liyanage N. Deepa Mounik Vvss Shivani Reddy Reddy Maddikunta Neelu Khare Thippa Reddy Gadekallu W. Hwang 41 55 0 20 Jan 2021