Terzis, Andreas

Poisoning Web-Scale Training Datasets is Practical

Carlini, N., Jagielski, M., Choquette-Choo, C. A., Paleka, D., Pearce, W., Anderson, H., Terzis, A., Thomas, K., & Tramèr, F. (2024) · 2024 IEEE Symposium on Security and Privacy (SP)

Adversarial Robustness in Machine LearningPrivacy-Preserving Technologies in Data

Cited by 138

Poisoning Web-Scale Training Datasets is Practical

Carlini, N., Jagielski, M., Choquette-Choo, C. A., Paleka, D., Pearce, W., Anderson, H., Terzis, A., Thomas, K., & Tramèr, F. (2023) · arXiv

Adversarial Robustness in Machine LearningPrivacy-Preserving Technologies in Data

Cited by 138

High Frequency Remote Monitoring of Parkinson's Disease via Smartphone: Platform Overview and Medication Response Detection

Zhan, A., Little, M. A., Harris, D. A., Abiola, S. O., Dorsey, E. R., Saria, S., & Terzis, A. (2016) · arXiv

Context-Aware Activity Recognition SystemsMobile Health and mHealth Applications

Cited by 50

Defeating Prompt Injections by Design

Debenedetti, E., Shumailov, I., Fan, T., Hayes, J., Carlini, N., Fabian, D., Kern, C., Shi, C., Terzis, A., & Tramèr, F. (2026) · 2026 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML)

Adversarial Robustness in Machine LearningSecurity and Verification in Computing

Cited by 15