AADMIP: Adversarial Attacks and Defenses Modeling in Industrial Processes. - Vitaliy Pozdnyakov; Aleksandr Kovalenko; Ilya Makarov; Mikhail Drobyshevskiy; Kirill S. Lukyanov (IJCAI, 2024)

Adversarial Attacks and Defenses in Automated Control Systems: A Comprehensive Benchmark. - Vitaliy Pozdnyakov; Aleksandr Kovalenko; Ilya Makarov; Mikhail Drobyshevskiy; Kirill S. Lukyanov (CoRR, 2024)

Graph Neural Network for Crawling Target Nodes in Social Networks. - Kirill S. Lukyanov; Mikhail Drobyshevskiy; Danil Shaikhelislamov; Denis Turdakov (CoRR, 2024)

Model Mimic Attack: Knowledge Distillation for Provably Transferable Adversarial Examples. - Kirill S. Lukyanov; Andrew I. Perminov; Denis Turdakov; Mikhail Pautov (CoRR, 2024)

Robustness questions the interpretability of graph neural networks: what to do? - Kirill S. Lukyanov; Georgii V. Sazonov; Serafim Boyarsky; Ilya Makarov (CoRR, 2025)

Framework GNN-AID: Graph Neural Network Analysis Interpretation and Defense. - Kirill S. Lukyanov; Mikhail Drobyshevskiy; Georgii V. Sazonov; Mikhail Soloviov; Ilya Makarov (CoRR, 2025)

The Defender's Dilemma: Are Defense Methods Against Different Attacks on Machine Learning Models Compatible? - Georgii V. Sazonov; Kirill S. Lukyanov; Igor N. Meleshin (Program. Comput. Softw., 2025)