31 citations · 36 across the 6 of their papers we have counts for
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cs.LG2021★ 31 cited
ML Attack Models: Adversarial Attacks and Data Poisoning Attacks
Jing Lin, Long Dang, Mohamed Rahouti +1
Many state-of-the-art ML models have outperformed humans in various tasks such as image classification. With such outstanding performance, ML models are widely used today. However,…
eess.SY2021
Mahalanobis distance-based robust approaches against false data injection attacks on dynamic power state estimation
Jing Lin, Kaiqi Xiong
Many researchers have studied false data injection (FDI) attacks in power state estimation, but existing state estimation approaches are still highly vulnerable to FDI attacks. In…
cs.LG2021★ 3 cited
Active Learning Under Malicious Mislabeling and Poisoning Attacks
Jing Lin, Ryan Luley, Kaiqi Xiong
Deep neural networks usually require large labeled datasets for training to achieve state-of-the-art performance in many tasks, such as image classification and natural language pr…