Towards Adversarial-Resilient Deep Neural Networks for False Data Injection Attack Detection in Power Grids

17 February 2021

Papers citing "Towards Adversarial-Resilient Deep Neural Networks for False Data Injection Attack Detection in Power Grids"

7 / 7 papers shown

Title
Risks of Practicing Large Language Models in Smart Grid: Threat Modeling and Validation Jiangnan Li Yingyuan Yang Jinyuan Stella Sun 57 3 0 10 May 2024
LESSON: Multi-Label Adversarial False Data Injection Attack for Deep Learning Locational Detection Jiwei Tian Chao Shen Buhong Wang Xiaofang Xia Meng Zhang Chenhao Lin Qian Li 23 36 0 29 Jan 2024
Vulnerability of Machine Learning Approaches Applied in IoT-based Smart Grid: A Review Zhenyong Zhang Mengxiang Liu Mingyang Sun Ruilong Deng Peng Cheng Dusit Niyato Mo-Yuen Chow Jiming Chen 26 37 0 30 Aug 2023
Mitigating Adversarial Effects of False Data Injection Attacks in Power Grid Farhin Farhad Riya Shahinul Hoque Jinyuan Stella Sun Jiangnan Li Hairong Qi Hairong Qi AAML AI4CE 32 0 0 29 Jan 2023
Defending Against Adversarial Attacks by Energy Storage Facility Jiawei Li Jianxiao Wang Lin Chen Yang Yu AAML 6 1 0 19 May 2022
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 256 3,108 0 04 Nov 2016
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 250 5,830 0 08 Jul 2016