21 citations · 22 across the 4 of their papers we have counts for
3 papers · 1 filter
Framework GNN-AID: Graph Neural Network Analysis Interpretation and Defense
Kirill Lukyanov, Mikhail Drobyshevskiy, Georgii Sazonov +2
The growing need for Trusted AI (TAI) highlights the importance of interpretability and robustness in machine learning models. However, many existing tools overlook graph data and…
Model Mimic Attack: Knowledge Distillation for Provably Transferable Adversarial Examples
Kirill Lukyanov, Andrew Perminov, Denis Turdakov +1
The vulnerability of artificial neural networks to adversarial perturbations in the black-box setting is widely studied in the literature. The majority of attack methods to constru…
Adversarial Attacks and Defenses in Fault Detection and Diagnosis: A Comprehensive Benchmark on the Tennessee Eastman Process
Vitaliy Pozdnyakov, Aleksandr Kovalenko, Ilya Makarov +2
Integrating machine learning into Automated Control Systems (ACS) enhances decision-making in industrial process management. One of the limitations to the widespread adoption of th…