| How to backdoor federated learning E Bagdasaryan, A Veit, Y Hua, D Estrin, V Shmatikov International conference on artificial intelligence and statistics, 2938-2948, 2020 | 2269 | 2020 |
| Differential privacy has disparate impact on model accuracy E Bagdasaryan, O Poursaeed, V Shmatikov Advances in neural information processing systems 32, 2019 | 562 | 2019 |
| Blind backdoors in deep learning models E Bagdasaryan, V Shmatikov 30th USENIX Security Symposium (USENIX Security 21), 1505-1521, 2021 | 331 | 2021 |
| Salvaging federated learning by local adaptation T Yu, E Bagdasaryan, V Shmatikov arXiv preprint arXiv:2002.04758, 2020 | 306 | 2020 |
| X-containers: Breaking down barriers to improve performance and isolation of cloud-native containers Z Shen, Z Sun, GE Sela, E Bagdasaryan, C Delimitrou, R Van Renesse, ... Proceedings of the Twenty-Fourth International Conference on Architectural …, 2019 | 110 | 2019 |
| Spinning language models: Risks of propaganda-as-a-service and countermeasures E Bagdasaryan, V Shmatikov 2022 IEEE Symposium on Security and Privacy (SP), 769-786, 2022 | 96* | 2022 |
| Openrec: A modular framework for extensible and adaptable recommendation algorithms L Yang, E Bagdasaryan, J Gruenstein, CK Hsieh, D Estrin Proceedings of the Eleventh ACM International Conference on Web Search and …, 2018 | 69 | 2018 |
| Towards sparse federated analytics: Location heatmaps under distributed differential privacy with secure aggregation E Bagdasaryan, P Kairouz, S Mellem, A Gascón, K Bonawitz, D Estrin, ... Proceedings on Privacy Enhancing Technologies 2022 (4), 162–182, 2022 | 29 | 2022 |
| Ancile: Enhancing privacy for ubiquitous computing with use-based privacy E Bagdasaryan, G Berlstein, J Waterman, E Birrell, N Foster, ... Proceedings of the 18th ACM Workshop on Privacy in the Electronic Society …, 2019 | 28 | 2019 |
| Abusing Images and Sounds for Indirect Instruction Injection in Multi-Modal LLMs E Bagdasaryan, TY Hsieh, B Nassi, V Shmatikov arXiv preprint arXiv:2307.10490 3, 2023 | 26 | 2023 |
| Derecho: Group communication at the speed of light J Behrens, K Birman, S Jha, M Milano, E Tremel, E Bagdasaryan, ... Technical Report. Cornell University, 2016 | 16 | 2016 |
| Ununlearning: Unlearning is not sufficient for content regulation in advanced generative ai I Shumailov, J Hayes, E Triantafillou, G Ortiz-Jimenez, N Papernot, ... arXiv preprint arXiv:2407.00106, 2024 | 9 | 2024 |
| Adversarial Illusions in Multi-Modal Embeddings E Bagdasaryan, V Shmatikov arXiv preprint arXiv:2308.11804, 2023 | 7 | 2023 |
| Air Gap: Protecting Privacy-Conscious Conversational Agents E Bagdasaryan, R Yi, S Ghalebikesabi, P Kairouz, M Gruteser, S Oh, ... arXiv preprint arXiv:2405.05175, 2024 | 4 | 2024 |
| Training a Tokenizer for Free with Private Federated Learning E Bagdasaryan, C Song, R van Dalen, M Seigel, Á Cahill ACL FL4NLP, 2022 | 4 | 2022 |
| Policy-based federated learning K Katevas, E Bagdasaryan, J Waterman, MM Safadieh, E Birrell, ... arXiv preprint arXiv:2003.06612, 2020 | 4 | 2020 |
| Operationalizing contextual integrity in privacy-conscious assistants S Ghalebikesabi, E Bagdasaryan, R Yi, I Yona, I Shumailov, A Pappu, ... arXiv preprint arXiv:2408.02373, 2024 | 2 | 2024 |
| Modularizing deep neural network-inspired recommendation algorithms L Yang, E Bagdasaryan, H Wen Proceedings of the 12th ACM Conference on Recommender Systems, 533-534, 2018 | 2 | 2018 |
| Soft Prompts Go Hard: Steering Visual Language Models with Hidden Meta-Instructions T Zhang, C Zhang, JX Morris, E Bagdasarian, V Shmatikov arXiv preprint arXiv:2407.08970, 2024 | 1 | 2024 |
| Injecting Bias in Text-To-Image Models via Composite-Trigger Backdoors A Naseh, J Roh, E Bagdasaryan, A Houmansadr arXiv e-prints, arXiv: 2406.15213, 2024 | 1 | 2024 |
Vitaly ShmatikovEmail verificata su cs.cornell.edu