Markpainting: Adversarial Machine Learning meets Inpainting. - David Khachaturov; Ilia Shumailov; Yiren Zhao; Nicolas Papernot; Ross J. Anderson (ICML, 2021)

Human-Producible Adversarial Examples. - David Khachaturov; Yue Gao 011; Ilia Shumailov; Robert D. Mullins; Ross J. Anderson; Kassem Fawaz (CoRR, 2023)

QBI: Quantile-based Bias Initialization for Efficient Private Data Reconstruction in Federated Learning. - Micha V. Nowak; Tim P. Bott; David Khachaturov; Frank Puppe; Adrian Krenzer; Amar Hekalo (CoRR, 2024)

Scaling Laws for Data Poisoning in LLMs. - Dillon Bowen; Brendan Murphy; Will Cai; David Khachaturov; Adam Gleave; Kellin Pelrine (CoRR, 2024)

Complexity Matters: Effective Dimensionality as a Measure for Adversarial Robustness. - David Khachaturov; Robert D. Mullins (CoRR, 2024)

Scaling Trends for Data Poisoning in LLMs. - Dillon Bowen; Brendan Murphy; Will Cai; David Khachaturov; Adam Gleave; Kellin Pelrine (AAAI, 2025)

"I am bad": Interpreting Stealthy, Universal and Robust Audio Jailbreaks in Audio-Language Models. - Isha Gupta; David Khachaturov; Robert D. Mullins (CoRR, 2025)

Watermarking Needs Input Repetition Masking. - David Khachaturov; Robert D. Mullins; Ilia Shumailov; Sumanth Dathathri (CoRR, 2025)

Adversarial Suffix Filtering: a Defense Pipeline for LLMs. - David Khachaturov; Robert D. Mullins (CoRR, 2025)

Governments Should Mandate Tiered Anonymity on Social-Media Platforms to Counter Deepfakes and LLM-Driven Mass Misinformation. - David Khachaturov; Roxanne Schnyder; Robert D. Mullins (CoRR, 2025)