Florian Tramèr

180 papers A* 54A 2B 1Journal 107Unranked 13

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	CaMeLs Can Use Computers Too: System-level Security for Computer Use Agents. CoRR Hanna Foerster, Robert Mullins, Tom Blanchard, Nicolas Papernot, Kristina Nikolic, Florian Tramèr, Ilia Shumailov, Cheng Zhang, Yiren Zhao
2026	J	`jnl`	Large-scale online deanonymization with LLMs. CoRR Simon Lermen, Daniel Paleka, Joshua Swanson, Michael Aerni, Nicholas Carlini, Florian Tramèr
2026	J	`jnl`	Learning to Inject: Automated Prompt Injection via Reinforcement Learning. CoRR Xin Chen, Jie Zhang, Florian Tramèr
2026	J	`jnl`	Reliable and Responsible Foundation Models: A Comprehensive Survey. CoRR Xinyu Yang, Junlin Han, Rishi Bommasani, Jinqi Luo, Wenjie Qu, Wangchunshu Zhou, Adel Bibi, Xiyao Wang, Jaehong Yoon, Elias Stengel-Eskin, Shengbang Tong, Lingfeng Shen, Rafael Rafailov, Runjia Li, Zhaoyang Wang, Yiyang Zhou, Chenhang Cui, Yu Wang, Wenhao Zheng, Huichi Zhou, Jindong Gu, Zhaorun Chen, Peng Xia, Tony Lee, Thomas P. Zollo, Vikash Sehwag, Jixuan Leng, Jiuhai Chen, Yuxin Wen, Huan Zhang, Zhun Deng, Linjun Zhang, Pavel Izmailov, Pang Wei Koh, Yulia Tsvetkov, Andrew Wilson, Jiaheng Zhang, James Zou, Cihang Xie, Hao Wang, Philip Torr, Julian J. McAuley, David Alvarez-Melis, Florian Tramèr, Kaidi Xu, Suman Jana, Chris Callison-Burch, René Vidal, Filippos Kokkinos, Mohit Bansal, Beidi Chen, Huaxiu Yao
2026	J	`jnl`	Representations of Text and Images Align From Layer One. CoRR Evzen Wybitul, Javier Rando, Florian Tramèr, Stanislav Fort
2026	J	`jnl`	Rethinking Benchmarks for Differentially Private Image Classification. CoRR Sabrina Mokhtari, Sara Kodeiri, Shubhankar Mohapatra, Florian Tramèr, Gautam Kamath
2025	J	`jnl`	Adversarial ML Problems Are Getting Harder to Solve and to Evaluate. CoRR Javier Rando, Jie Zhang, Nicholas Carlini, Florian Tramèr
2025	A*	`conf`	Adversarial Perturbations Cannot Reliably Protect Artists From Generative AI. ICLR Robert Hönig, Javier Rando, Nicholas Carlini, Florian Tramèr
2025	A*	`conf`	Adversarial Search Engine Optimization for Large Language Models. ICLR Fredrik Nestaas, Edoardo Debenedetti, Florian Tramèr
2025	J	`jnl`	An Adversarial Perspective on Machine Unlearning for AI Safety. Trans. Mach. Learn. Res. Jakub Lucki, Boyi Wei, Yangsibo Huang, Peter Henderson, Florian Tramèr, Javier Rando
2025	A*	`conf`	AutoAdvExBench: Benchmarking Autonomous Exploitation of Adversarial Example Defenses. ICML Nicholas Carlini, Edoardo Debenedetti, Javier Rando, Milad Nasr, Florian Tramèr
2025	J	`jnl`	AutoAdvExBench: Benchmarking autonomous exploitation of adversarial example defenses. CoRR Nicholas Carlini, Javier Rando, Edoardo Debenedetti, Milad Nasr, Florian Tramèr
2025	J	`jnl`	Black-box Optimization of LLM Outputs by Asking for Directions. CoRR Jie Zhang, Meng Ding, Yang Liu, Jue Hong, Florian Tramèr
2025	J	`jnl`	Can Reasoning Models Obfuscate Reasoning? Stress-Testing Chain-of-Thought Monitorability. CoRR Artur Zolkowski, Wen Xing, David Lindner, Florian Tramèr, Erik Jenner
2025	A*	`conf`	Consistency Checks for Language Model Forecasters. ICLR Daniel Paleka, Abhimanyu Pallavi Sudhir, Alejandro Alvarez, Vineeth Bhat, Adam Shen, Evan Wang, Florian Tramèr
2025	J	`jnl`	Defeating Prompt Injections by Design. CoRR Edoardo Debenedetti, Ilia Shumailov, Tianqi Fan, Jamie Hayes, Nicholas Carlini, Daniel Fabian, Christoph Kern, Chongyang Shi, Andreas Terzis, Florian Tramèr
2025	J	`jnl`	Design Patterns for Securing LLM Agents against Prompt Injections. CoRR Luca Beurer-Kellner, Beat Buesser, Ana-Maria Cretu, Edoardo Debenedetti, Daniel Dobos, Daniel Fabian, Marc Fischer, David Froelicher, Kathrin Grosse, Daniel Naeff, Ezinwanne Ozoani, Andrew Paverd, Florian Tramèr, Václav Volhejn
2025	A*	`conf`	Exploring and Mitigating Adversarial Manipulation of Voting-Based Leaderboards. ICML Yangsibo Huang, Milad Nasr, Anastasios Nikolas Angelopoulos, Nicholas Carlini, Wei-Lin Chiang, Christopher A. Choquette-Choo, Daphne Ippolito, Matthew Jagielski, Katherine Lee, Ken Liu, Ion Stoica, Florian Tramèr, Chiyuan Zhang
2025	J	`jnl`	Exploring and Mitigating Adversarial Manipulation of Voting-Based Leaderboards. CoRR Yangsibo Huang, Milad Nasr, Anastasios Angelopoulos, Nicholas Carlini, Wei-Lin Chiang, Christopher A. Choquette-Choo, Daphne Ippolito, Matthew Jagielski, Katherine Lee, Ken Ziyu Liu, Ion Stoica, Florian Tramèr, Chiyuan Zhang
2025	J	`jnl`	International AI Safety Report. CoRR Yoshua Bengio, Sören Mindermann, Daniel Privitera, Tamay Besiroglu, Rishi Bommasani, Stephen Casper, Yejin Choi, Philip Fox, Ben Garfinkel, Danielle Goldfarb, Hoda Heidari, Anson Ho, Sayash Kapoor, Leila Khalatbari, Shayne Longpre, Sam Manning, Vasilios Mavroudis, Mantas Mazeika, Julian Michael, Jessica Newman, Kwan Yee Ng, Chinasa T. Okolo, Inioluwa Deborah Raji, Girish Sastry, Elizabeth Seger, Theodora Skeadas, Tobin South, Emma Strubell, Florian Tramèr, Lucia Velasco, Nicole Wheeler, Daron Acemoglu, Olubayo Adekanmbi, David Dalrymple, Thomas G. Dietterich, Edward W. Felten, Pascale Fung, Pierre-Olivier Gourinchas, Fredrik Heintz, Geoffrey E. Hinton, Nick R. Jennings, Andreas Krause, Susan Leavy, Percy Liang, Teresa Ludermir, Vidushi Marda, Helen Margetts, John A. McDermid, Jane Munga, Arvind Narayanan, Alondra Nelson, Clara Neppel, Alice Oh, Gopal Ramchurn, Stuart Russell, Marietje Schaake, Bernhard Schölkopf, Dawn Song, Alvaro Soto, Lee Tiedrich, Gaël Varoquaux, Andrew Yao, Ya-Qin Zhang, Fahad Albalawi, Marwan Alserkal, Olubunmi Ajala, Guillaume Avrin, Christian Busch, André Carlos Ponce de Leon Ferreira de Carvalho, Bronwyn Fox, Amandeep Singh Gill, Ahmet Halit Hatip, Juha Heikkilä, Gill Jolly, Ziv Katzir, Hiroaki Kitano, Antonio Krüger, Chris Johnson, Saif M. Khan, Kyoung Mu Lee, Dominic Vincent Ligot, Oleksii Molchanovskyi, Andrea Monti, Nusu Mwamanzi, Mona Nemer, Nuria Oliver, José Ramón López Portillo, Balaraman Ravindran, Raquel Pezoa Rivera, Hammam Riza, Crystal Rugege, Ciarán Seoighe, Jerry Sheehan, Haroon Sheikh, Denise Wong, Yi Zeng
2025	J	`jnl`	LLMs unlock new paths to monetizing exploits. CoRR Nicholas Carlini, Milad Nasr, Edoardo Debenedetti, Barry Wang, Christopher A. Choquette-Choo, Daphne Ippolito, Florian Tramèr, Matthew Jagielski
2025	A*	`conf`	Measuring Non-Adversarial Reproduction of Training Data in Large Language Models. ICLR Michael Aerni, Javier Rando, Edoardo Debenedetti, Nicholas Carlini, Daphne Ippolito, Florian Tramèr
2025	—	`conf`	Membership Inference Attacks on Sequence Models. SP (Workshops) Lorenzo Rossi, Michael Aerni, Jie Zhang, Florian Tramèr
2025	J	`jnl`	Membership Inference Attacks on Sequence Models. CoRR Lorenzo Rossi, Michael Aerni, Jie Zhang, Florian Tramèr
2025	J	`jnl`	Modal Aphasia: Can Unified Multimodal Models Describe Images From Memory? CoRR Michael Aerni, Joshua Swanson, Kristina Nikolic, Florian Tramèr
2025	A*	`conf`	Persistent Pre-training Poisoning of LLMs. ICLR Yiming Zhang, Javier Rando, Ivan Evtimov, Jianfeng Chi, Eric Michael Smith, Nicholas Carlini, Florian Tramèr, Daphne Ippolito
2025	J	`jnl`	Pitfalls in Evaluating Language Model Forecasters. CoRR Daniel Paleka, Shashwat Goel, Jonas Geiping, Florian Tramèr
2025	—	`conf`	Position: Membership Inference Attacks Cannot Prove That a Model was Trained on Your Data. SaTML Jie Zhang, Debeshee Das, Gautam Kamath, Florian Tramèr
2025	J	`jnl`	RealMath: A Continuous Benchmark for Evaluating Language Models on Research-Level Mathematics. CoRR Jie Zhang, Cezara Petrui, Kristina Nikolic, Florian Tramèr
2025	J	`jnl`	Reliable and Responsible Foundation Models. Trans. Mach. Learn. Res. Xinyu Yang, Junlin Han, Rishi Bommasani, Jinqi Luo, Wenjie Qu, Wangchunshu Zhou, Adel Bibi, Xiyao Wang, Jaehong Yoon, Elias Stengel-Eskin, Shengbang Tong, Lingfeng Shen, Rafael Rafailov, Runjia Li, Zhaoyang Wang, Yiyang Zhou, Chenhang Cui, Yu Wang, Wenhao Zheng, Huichi Zhou, Jindong Gu, Zhaorun Chen, Peng Xia, Tony Lee, Thomas P. Zollo, Vikash Sehwag, Jixuan Leng, Jiuhai Chen, Yuxin Wen, Huan Zhang, Zhun Deng, Linjun Zhang, Pavel Izmailov, Pang Wei Koh, Yulia Tsvetkov, Andrew Gordon Wilson, Jiaheng Zhang, James Zou, Cihang Xie, Hao Wang, Philip Torr, Julian J. McAuley, David Alvarez-Melis, Florian Tramèr, Kaidi Xu, Suman Jana, Chris Callison-Burch, René Vidal, Filippos Kokkinos, Mohit Bansal, Beidi Chen, Huaxiu Yao
2025	A*	`conf`	Scalable Extraction of Training Data from Aligned, Production Language Models. ICLR Milad Nasr, Javier Rando, Nicholas Carlini, Jonathan Hayase, Matthew Jagielski, A. Feder Cooper, Daphne Ippolito, Christopher A. Choquette-Choo, Florian Tramèr, Katherine Lee
2025	A*	`conf`	SoK: Watermarking for AI-Generated Content. SP Xuandong Zhao, Sam Gunn, Miranda Christ, Jaiden Fairoze, Andrés Fábrega, Nicholas Carlini, Sanjam Garg, Sanghyun Hong, Milad Nasr, Florian Tramèr, Somesh Jha, Lei Li, Yu-Xiang Wang, Dawn Song
2025	J	`jnl`	The Attacker Moves Second: Stronger Adaptive Attacks Bypass Defenses Against Llm Jailbreaks and Prompt Injections. CoRR Milad Nasr, Nicholas Carlini, Chawin Sitawarin, Sander V. Schulhoff, Jamie Hayes, Michael Ilie, Juliette Pluto, Shuang Song, Harsh Chaudhari, Ilia Shumailov, Abhradeep Thakurta, Kai Yuanqing Xiao, Andreas Terzis, Florian Tramèr
2025	A*	`conf`	The Jailbreak Tax: How Useful are Your Jailbreak Outputs? ICML Kristina Nikolic, Luze Sun, Jie Zhang, Florian Tramèr
2025	J	`jnl`	The Jailbreak Tax: How Useful are Your Jailbreak Outputs? CoRR Kristina Nikolic, Luze Sun, Jie Zhang, Florian Tramèr
2024	J	`jnl`	Adversarial Perturbations Cannot Reliably Protect Artists From Generative AI. CoRR Robert Hönig, Javier Rando, Nicholas Carlini, Florian Tramèr
2024	J	`jnl`	Adversarial Search Engine Optimization for Large Language Models. CoRR Fredrik Nestaas, Edoardo Debenedetti, Florian Tramèr
2024	J	`jnl`	AgentDojo: A Dynamic Environment to Evaluate Attacks and Defenses for LLM Agents. CoRR Edoardo Debenedetti, Jie Zhang, Mislav Balunovic, Luca Beurer-Kellner, Marc Fischer, Florian Tramèr
2024	A*	`conf`	AgentDojo: A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents. NeurIPS Edoardo Debenedetti, Jie Zhang, Mislav Balunovic, Luca Beurer-Kellner, Marc Fischer, Florian Tramèr
2024	J	`jnl`	An Adversarial Perspective on Machine Unlearning for AI Safety. CoRR Jakub Lucki, Boyi Wei, Yangsibo Huang, Peter Henderson, Florian Tramèr, Javier Rando
2024	J	`jnl`	Blind Baselines Beat Membership Inference Attacks for Foundation Models. CoRR Debeshee Das, Jie Zhang, Florian Tramèr
2024	J	`jnl`	Competition Report: Finding Universal Jailbreak Backdoors in Aligned LLMs. CoRR Javier Rando, Francesco Croce, Krystof Mitka, Stepan Shabalin, Maksym Andriushchenko, Nicolas Flammarion, Florian Tramèr
2024	J	`jnl`	Consistency Checks for Language Model Forecasters. CoRR Daniel Paleka, Abhimanyu Pallavi Sudhir, Alejandro Alvarez, Vineeth Bhat, Adam Shen, Evan Wang, Florian Tramèr
2024	A*	`conf`	Dataset and Lessons Learned from the 2024 SaTML LLM Capture-the-Flag Competition. NeurIPS Edoardo Debenedetti, Javier Rando, Daniel Paleka, Silaghi Fineas Florin, Dragos Albastroiu, Niv Cohen, Yuval Lemberg, Reshmi Ghosh, Rui Wen, Ahmed Salem, Giovanni Cherubin, Santiago Zanella-Béguelin, Robin Schmid, Victor Klemm, Takahiro Miki, Chenhao Li, Stefan Kraft, Mario Fritz, Florian Tramèr, Sahar Abdelnabi, Lea Schönherr
2024	J	`jnl`	Dataset and Lessons Learned from the 2024 SaTML LLM Capture-the-Flag Competition. CoRR Edoardo Debenedetti, Javier Rando, Daniel Paleka, Silaghi Fineas Florin, Dragos Albastroiu, Niv Cohen, Yuval Lemberg, Reshmi Ghosh, Rui Wen, Ahmed Salem, Giovanni Cherubin, Santiago Zanella-Béguelin, Robin Schmid, Victor Klemm, Takahiro Miki, Chenhao Li, Stefan Kraft, Mario Fritz, Florian Tramèr, Sahar Abdelnabi, Lea Schönherr
2024	—	`conf`	Evading Black-box Classifiers Without Breaking Eggs. SaTML Edoardo Debenedetti, Nicholas Carlini, Florian Tramèr
2024	—	`conf`	Evaluating Superhuman Models with Consistency Checks. SaTML Lukas Fluri, Daniel Paleka, Florian Tramèr
2024	A*	`conf`	Evaluations of Machine Learning Privacy Defenses are Misleading. CCS Michael Aerni, Jie Zhang, Florian Tramèr
2024	J	`jnl`	Evaluations of Machine Learning Privacy Defenses are Misleading. CoRR Michael Aerni, Jie Zhang, Florian Tramèr
2024	A*	`conf`	Extracting Training Data From Document-Based VQA Models. ICML Francesco Pinto, Nathalie Rauschmayr, Florian Tramèr, Philip Torr, Federico Tombari
2024	J	`jnl`	Extracting Training Data from Document-Based VQA Models. CoRR Francesco Pinto, Nathalie Rauschmayr, Florian Tramèr, Philip Torr, Federico Tombari
2024	J	`jnl`	Foundational Challenges in Assuring Alignment and Safety of Large Language Models. CoRR Usman Anwar, Abulhair Saparov, Javier Rando, Daniel Paleka, Miles Turpin, Peter Hase, Ekdeep Singh Lubana, Erik Jenner, Stephen Casper, Oliver Sourbut, Benjamin L. Edelman, Zhaowei Zhang, Mario Günther, Anton Korinek, José Hernández-Orallo, Lewis Hammond, Eric J. Bigelow, Alexander Pan, Lauro Langosco, Tomasz Korbak, Heidi C. Zhang, Ruiqi Zhong, Seán Ó hÉigeartaigh, Gabriel Recchia, Giulio Corsi, Alan Chan, Markus Anderljung, Lilian Edwards, Yoshua Bengio, Danqi Chen, Samuel Albanie, Tegan Maharaj, Jakob N. Foerster, Florian Tramèr, He He, Atoosa Kasirzadeh, Yejin Choi, David Krueger
2024	J	`jnl`	Foundational Challenges in Assuring Alignment and Safety of Large Language Models. Trans. Mach. Learn. Res. Usman Anwar, Abulhair Saparov, Javier Rando, Daniel Paleka, Miles Turpin, Peter Hase, Ekdeep Singh Lubana, Erik Jenner, Stephen Casper, Oliver Sourbut, Benjamin L. Edelman, Zhaowei Zhang, Mario Günther, Anton Korinek, José Hernández-Orallo, Lewis Hammond, Eric J. Bigelow, Alexander Pan, Lauro Langosco, Tomasz Korbak, Heidi Chenyu Zhang, Ruiqi Zhong, Seán Ó hÉigeartaigh, Gabriel Recchia, Giulio Corsi, Alan Chan, Markus Anderljung, Lilian Edwards, Aleksandar Petrov, Christian Schröder de Witt, Sumeet Ramesh Motwani, Yoshua Bengio, Danqi Chen, Philip Torr, Samuel Albanie, Tegan Maharaj, Jakob Nicolaus Foerster, Florian Tramèr, He He, Atoosa Kasirzadeh, Yejin Choi, David Krueger
2024	J	`jnl`	Gradient Masking All-at-Once: Ensemble Everything Everywhere Is Not Robust. CoRR Jie Zhang, Kristina Nikolic, Nicholas Carlini, Florian Tramèr
2024	J	`jnl`	Gradient-based Jailbreak Images for Multimodal Fusion Models. CoRR Javier Rando, Hannah Korevaar, Erik Brinkman, Ivan Evtimov, Florian Tramèr
2024	J	`jnl`	International Scientific Report on the Safety of Advanced AI (Interim Report). CoRR Yoshua Bengio, Sören Mindermann, Daniel Privitera, Tamay Besiroglu, Rishi Bommasani, Stephen Casper, Yejin Choi, Danielle Goldfarb, Hoda Heidari, Leila Khalatbari, Shayne Longpre, Vasilios Mavroudis, Mantas Mazeika, Kwan Yee Ng, Chinasa T. Okolo, Inioluwa Deborah Raji, Theodora Skeadas, Florian Tramèr, Bayo Adekanmbi, Paul F. Christiano, David Dalrymple, Thomas G. Dietterich, Edward W. Felten, Pascale Fung, Pierre-Olivier Gourinchas, Nick R. Jennings, Andreas Krause, Percy Liang, Teresa Ludermir, Vidushi Marda, Helen Margetts, John A. McDermid, Arvind Narayanan, Alondra Nelson, Alice Oh, Gopal Ramchurn, Stuart Russell, Marietje Schaake, Dawn Song, Alvaro Soto, Lee Tiedrich, Gaël Varoquaux, Andrew Yao, Ya-Qin Zhang
2024	A*	`conf`	JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language Models. NeurIPS Patrick Chao, Edoardo Debenedetti, Alexander Robey, Maksym Andriushchenko, Francesco Croce, Vikash Sehwag, Edgar Dobriban, Nicolas Flammarion, George J. Pappas, Florian Tramèr, Hamed Hassani, Eric Wong
2024	J	`jnl`	JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language Models. CoRR Patrick Chao, Edoardo Debenedetti, Alexander Robey, Maksym Andriushchenko, Francesco Croce, Vikash Sehwag, Edgar Dobriban, Nicolas Flammarion, George J. Pappas, Florian Tramèr, Hamed Hassani, Eric Wong
2024	J	`jnl`	Measuring Non-Adversarial Reproduction of Training Data in Large Language Models. CoRR Michael Aerni, Javier Rando, Edoardo Debenedetti, Nicholas Carlini, Daphne Ippolito, Florian Tramèr
2024	J	`jnl`	Membership Inference Attacks Cannot Prove that a Model Was Trained On Your Data. CoRR Jie Zhang, Debeshee Das, Gautam Kamath, Florian Tramèr
2024	J	`jnl`	Persistent Pre-Training Poisoning of LLMs. CoRR Yiming Zhang, Javier Rando, Ivan Evtimov, Jianfeng Chi, Eric Michael Smith, Nicholas Carlini, Florian Tramèr, Daphne Ippolito
2024	A*	`conf`	Poisoning Web-Scale Training Datasets is Practical. SP Nicholas Carlini, Matthew Jagielski, Christopher A. Choquette-Choo, Daniel Paleka, Will Pearce, Hyrum S. Anderson, Andreas Terzis, Kurt Thomas, Florian Tramèr
2024	A*	`conf`	Position: Considerations for Differentially Private Learning with Large-Scale Public Pretraining. ICML Florian Tramèr, Gautam Kamath, Nicholas Carlini
2024	A*	`conf`	Privacy Backdoors: Stealing Data with Corrupted Pretrained Models. ICML Shanglun Feng, Florian Tramèr
2024	J	`jnl`	Privacy Backdoors: Stealing Data with Corrupted Pretrained Models. CoRR Shanglun Feng, Florian Tramèr
2024	A*	`conf`	Privacy Side Channels in Machine Learning Systems. USENIX Security Symposium Edoardo Debenedetti, Giorgio Severi, Milad Nasr, Christopher A. Choquette-Choo, Matthew Jagielski, Eric Wallace, Nicholas Carlini, Florian Tramèr
2024	A*	`conf`	Query-Based Adversarial Prompt Generation. NeurIPS Jonathan Hayase, Ema Borevkovic, Nicholas Carlini, Florian Tramèr, Milad Nasr
2024	J	`jnl`	Query-Based Adversarial Prompt Generation. CoRR Jonathan Hayase, Ema Borevkovic, Nicholas Carlini, Florian Tramèr, Milad Nasr
2024	J	`jnl`	SoK: Watermarking for AI-Generated Content. CoRR Xuandong Zhao, Sam Gunn, Miranda Christ, Jaiden Fairoze, Andrés Fábrega, Nicholas Carlini, Sanjam Garg, Sanghyun Hong, Milad Nasr, Florian Tramèr, Somesh Jha, Lei Li, Yu-Xiang Wang, Dawn Song
2024	J	`jnl`	Stealing Part of a Production Language Model. CoRR Nicholas Carlini, Daniel Paleka, Krishnamurthy (Dj) Dvijotham, Thomas Steinke, Jonathan Hayase, A. Feder Cooper, Katherine Lee, Matthew Jagielski, Milad Nasr, Arthur Conmy, Eric Wallace, David Rolnick, Florian Tramèr
2024	A*	`conf`	Stealing part of a production language model. ICML Nicholas Carlini, Daniel Paleka, Krishnamurthy Dj Dvijotham, Thomas Steinke, Jonathan Hayase, A. Feder Cooper, Katherine Lee, Matthew Jagielski, Milad Nasr, Arthur Conmy, Eric Wallace, David Rolnick, Florian Tramèr
2024	A*	`conf`	Universal Jailbreak Backdoors from Poisoned Human Feedback. ICLR Javier Rando, Florian Tramèr
2023	A*	`conf`	(Certified!!) Adversarial Robustness for Free! ICLR Nicholas Carlini, Florian Tramèr, Krishnamurthy (Dj) Dvijotham, Leslie Rice, Mingjie Sun, J. Zico Kolter
2023	A*	`conf`	Are aligned neural networks adversarially aligned? NeurIPS Nicholas Carlini, Milad Nasr, Christopher A. Choquette-Choo, Matthew Jagielski, Irena Gao, Pang Wei Koh, Daphne Ippolito, Florian Tramèr, Ludwig Schmidt
2023	J	`jnl`	Are aligned neural networks adversarially aligned? CoRR Nicholas Carlini, Milad Nasr, Christopher A. Choquette-Choo, Matthew Jagielski, Irena Gao, Anas Awadalla, Pang Wei Koh, Daphne Ippolito, Katherine Lee, Florian Tramèr, Ludwig Schmidt
2023	J	`jnl`	Backdoor Attacks for In-Context Learning with Language Models. CoRR Nikhil Kandpal, Matthew Jagielski, Florian Tramèr, Nicholas Carlini
2023	A*	`conf`	Counterfactual Memorization in Neural Language Models. NeurIPS Chiyuan Zhang, Daphne Ippolito, Katherine Lee, Matthew Jagielski, Florian Tramèr, Nicholas Carlini
2023	J	`jnl`	Evading Black-box Classifiers Without Breaking Eggs. CoRR Edoardo Debenedetti, Nicholas Carlini, Florian Tramèr
2023	J	`jnl`	Evaluating Superhuman Models with Consistency Checks. CoRR Lukas Fluri, Daniel Paleka, Florian Tramèr
2023	A*	`conf`	Extracting Training Data from Diffusion Models. USENIX Security Symposium Nicholas Carlini, Jamie Hayes, Milad Nasr, Matthew Jagielski, Vikash Sehwag, Florian Tramèr, Borja Balle, Daphne Ippolito, Eric Wallace
2023	J	`jnl`	Extracting Training Data from Diffusion Models. CoRR Nicholas Carlini, Jamie Hayes, Milad Nasr, Matthew Jagielski, Vikash Sehwag, Florian Tramèr, Borja Balle, Daphne Ippolito, Eric Wallace
2023	A*	`conf`	Measuring Forgetting of Memorized Training Examples. ICLR Matthew Jagielski, Om Thakkar, Florian Tramèr, Daphne Ippolito, Katherine Lee, Nicholas Carlini, Eric Wallace, Shuang Song, Abhradeep Guha Thakurta, Nicolas Papernot, Chiyuan Zhang
2023	J	`jnl`	Poisoning Web-Scale Training Datasets is Practical. CoRR Nicholas Carlini, Matthew Jagielski, Christopher A. Choquette-Choo, Daniel Paleka, Will Pearce, Hyrum S. Anderson, Andreas Terzis, Kurt Thomas, Florian Tramèr
2023	A*	`conf`	Preprocessors Matter! Realistic Decision-Based Attacks on Machine Learning Systems. ICML Chawin Sitawarin, Florian Tramèr, Nicholas Carlini
2023	B	`conf`	Preventing Generation of Verbatim Memorization in Language Models Gives a False Sense of Privacy. INLG Daphne Ippolito, Florian Tramèr, Milad Nasr, Chiyuan Zhang, Matthew Jagielski, Katherine Lee, Christopher A. Choquette-Choo, Nicholas Carlini
2023	J	`jnl`	Privacy Side Channels in Machine Learning Systems. CoRR Edoardo Debenedetti, Giorgio Severi, Nicholas Carlini, Christopher A. Choquette-Choo, Matthew Jagielski, Milad Nasr, Eric Wallace, Florian Tramèr
2023	—	`ed.`	Proceedings of the 16th ACM Workshop on Artificial Intelligence and Security, AISec 2023, Copenhagen, Denmark, 30 November 2023 AISec@CCS Maura Pintor, Xinyun Chen, Florian Tramèr
2023	A*	`conf`	Quantifying Memorization Across Neural Language Models. ICLR Nicholas Carlini, Daphne Ippolito, Matthew Jagielski, Katherine Lee, Florian Tramèr, Chiyuan Zhang
2023	J	`jnl`	Randomness in ML Defenses Helps Persistent Attackers and Hinders Evaluators. CoRR Keane Lucas, Matthew Jagielski, Florian Tramèr, Lujo Bauer, Nicholas Carlini
2023	A*	`conf`	SNAP: Efficient Extraction of Private Properties with Poisoning. SP Harsh Chaudhari, John Abascal, Alina Oprea, Matthew Jagielski, Florian Tramèr, Jonathan R. Ullman
2023	J	`jnl`	Scalable Extraction of Training Data from (Production) Language Models. CoRR Milad Nasr, Nicholas Carlini, Jonathan Hayase, Matthew Jagielski, A. Feder Cooper, Daphne Ippolito, Christopher A. Choquette-Choo, Eric Wallace, Florian Tramèr, Katherine Lee
2023	A*	`conf`	Students Parrot Their Teachers: Membership Inference on Model Distillation. NeurIPS Matthew Jagielski, Milad Nasr, Katherine Lee, Christopher A. Choquette-Choo, Nicholas Carlini, Florian Tramèr
2023	A*	`conf`	Tight Auditing of Differentially Private Machine Learning. USENIX Security Symposium Milad Nasr, Jamie Hayes, Thomas Steinke, Borja Balle, Florian Tramèr, Matthew Jagielski, Nicholas Carlini, Andreas Terzis
2023	J	`jnl`	Tight Auditing of Differentially Private Machine Learning. CoRR Milad Nasr, Jamie Hayes, Thomas Steinke, Borja Balle, Florian Tramèr, Matthew Jagielski, Nicholas Carlini, Andreas Terzis
2023	J	`jnl`	Universal Jailbreak Backdoors from Poisoned Human Feedback. CoRR Javier Rando, Florian Tramèr
2022	J	`jnl`	(Certified!!) Adversarial Robustness for Free! CoRR Nicholas Carlini, Florian Tramèr, Krishnamurthy Dvijotham, J. Zico Kolter
2022	A*	`conf`	AISec '22: 15th ACM Workshop on Artificial Intelligence and Security. CCS Ambra Demontis, Xinyun Chen, Florian Tramèr
2022	J	`jnl`	Considerations for Differentially Private Learning with Large-Scale Public Pretraining. CoRR Florian Tramèr, Gautam Kamath, Nicholas Carlini
2022	A*	`conf`	Data Poisoning Won't Save You From Facial Recognition. ICLR Evani Radiya-Dixit, Sanghyun Hong, Nicholas Carlini, Florian Tramèr
2022	J	`jnl`	Debugging Differential Privacy: A Case Study for Privacy Auditing. CoRR Florian Tramèr, Andreas Terzis, Thomas Steinke, Shuang Song, Matthew Jagielski, Nicholas Carlini
2022	A*	`conf`	Detecting Adversarial Examples Is (Nearly) As Hard As Classifying Them. ICML Florian Tramèr
2022	A*	`conf`	Increasing Confidence in Adversarial Robustness Evaluations. NeurIPS Roland S. Zimmermann, Wieland Brendel, Florian Tramèr, Nicholas Carlini
2022	J	`jnl`	Increasing Confidence in Adversarial Robustness Evaluations. CoRR Roland S. Zimmermann, Wieland Brendel, Florian Tramèr, Nicholas Carlini
2022	A*	`conf`	Large Language Models Can Be Strong Differentially Private Learners. ICLR Xuechen Li, Florian Tramèr, Percy Liang, Tatsunori Hashimoto
2022	J	`jnl`	Measuring Forgetting of Memorized Training Examples. CoRR Matthew Jagielski, Om Thakkar, Florian Tramèr, Daphne Ippolito, Katherine Lee, Nicholas Carlini, Eric Wallace, Shuang Song, Abhradeep Thakurta, Nicolas Papernot, Chiyuan Zhang
2022	A*	`conf`	Membership Inference Attacks From First Principles. SP Nicholas Carlini, Steve Chien, Milad Nasr, Shuang Song, Andreas Terzis, Florian Tramèr
2022	J	`jnl`	Preprocessors Matter! Realistic Decision-Based Attacks on Machine Learning Systems. CoRR Chawin Sitawarin, Florian Tramèr, Nicholas Carlini
2022	J	`jnl`	Preventing Verbatim Memorization in Language Models Gives a False Sense of Privacy. CoRR Daphne Ippolito, Florian Tramèr, Milad Nasr, Chiyuan Zhang, Matthew Jagielski, Katherine Lee, Christopher A. Choquette-Choo, Nicholas Carlini
2022	—	`ed.`	Proceedings of the 15th ACM Workshop on Artificial Intelligence and Security, AISec 2022, Los Angeles, CA, USA, 11 November 2022 AISec@CCS Ambra Demontis, Xinyun Chen, Florian Tramèr
2022	J	`jnl`	Quantifying Memorization Across Neural Language Models. CoRR Nicholas Carlini, Daphne Ippolito, Matthew Jagielski, Katherine Lee, Florian Tramèr, Chiyuan Zhang
2022	J	`jnl`	Red-Teaming the Stable Diffusion Safety Filter. CoRR Javier Rando, Daniel Paleka, David Lindner, Lennart Heim, Florian Tramèr
2022	J	`jnl`	SNAP: Efficient Extraction of Private Properties with Poisoning. CoRR Harsh Chaudhari, John Abascal, Alina Oprea, Matthew Jagielski, Florian Tramèr, Jonathan R. Ullman
2022	A*	`conf`	The Privacy Onion Effect: Memorization is Relative. NeurIPS Nicholas Carlini, Matthew Jagielski, Chiyuan Zhang, Nicolas Papernot, Andreas Terzis, Florian Tramèr
2022	J	`jnl`	The Privacy Onion Effect: Memorization is Relative. CoRR Nicholas Carlini, Matthew Jagielski, Chiyuan Zhang, Nicolas Papernot, Andreas Terzis, Florian Tramèr
2022	A*	`conf`	Truth Serum: Poisoning Machine Learning Models to Reveal Their Secrets. CCS Florian Tramèr, Reza Shokri, Ayrton San Joaquin, Hoang Le, Matthew Jagielski, Sanghyun Hong, Nicholas Carlini
2022	J	`jnl`	Truth Serum: Poisoning Machine Learning Models to Reveal Their Secrets. CoRR Florian Tramèr, Reza Shokri, Ayrton San Joaquin, Hoang Le, Matthew Jagielski, Sanghyun Hong, Nicholas Carlini
2022	—	`conf`	What Does it Mean for a Language Model to Preserve Privacy? FAccT Hannah Brown, Katherine Lee, Fatemehsadat Mireshghallah, Reza Shokri, Florian Tramèr
2022	J	`jnl`	What Does it Mean for a Language Model to Preserve Privacy? CoRR Hannah Brown, Katherine Lee, Fatemehsadat Mireshghallah, Reza Shokri, Florian Tramèr
2021	J	`jnl`	Advances and Open Problems in Federated Learning. Found. Trends Mach. Learn. Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Kallista A. Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D'Oliveira, Hubert Eichner, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adrià Gascón, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaïd Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konecný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Hang Qi, Daniel Ramage, Ramesh Raskar, Mariana Raykova, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao
2021	A*	`conf`	Antipodes of Label Differential Privacy: PATE and ALIBI. NeurIPS Mani Malek Esmaeili, Ilya Mironov, Karthik Prasad, Igor Shilov, Florian Tramèr
2021	J	`jnl`	Antipodes of Label Differential Privacy: PATE and ALIBI. CoRR Mani Malek, Ilya Mironov, Karthik Prasad, Igor Shilov, Florian Tramèr
2021	J	`jnl`	Counterfactual Memorization in Neural Language Models. CoRR Chiyuan Zhang, Daphne Ippolito, Katherine Lee, Matthew Jagielski, Florian Tramèr, Nicholas Carlini
2021	J	`jnl`	Data Poisoning Won't Save You From Facial Recognition. CoRR Evani Radiya-Dixit, Florian Tramèr
2021	J	`jnl`	Detecting Adversarial Examples Is (Nearly) As Hard As Classifying Them. CoRR Florian Tramèr
2021	A*	`conf`	Differentially Private Learning Needs Better Features (or Much More Data). ICLR Florian Tramèr, Dan Boneh
2021	A*	`conf`	Extracting Training Data from Large Language Models. USENIX Security Symposium Nicholas Carlini, Florian Tramèr, Eric Wallace, Matthew Jagielski, Ariel Herbert-Voss, Katherine Lee, Adam Roberts, Tom B. Brown, Dawn Song, Úlfar Erlingsson, Alina Oprea, Colin Raffel
2021	—	`conf`	Fourth International Workshop on Dependable and Secure Machine Learning - DSML 2021. DSN Workshops Hui Xu, Guanpeng Li, Homa Alemzadeh, Rakesh Bobba, Varun Chandrasekaran, David E. Evans, Nicolas Papernot, Karthik Pattabiraman, Florian Tramèr
2021	A*	`conf`	Is Private Learning Possible with Instance Encoding? SP Nicholas Carlini, Samuel Deng, Sanjam Garg, Somesh Jha, Saeed Mahloujifar, Mohammad Mahmoody, Abhradeep Thakurta, Florian Tramèr
2021	A*	`conf`	Label-Only Membership Inference Attacks. ICML Christopher A. Choquette-Choo, Florian Tramèr, Nicholas Carlini, Nicolas Papernot
2021	J	`jnl`	Large Language Models Can Be Strong Differentially Private Learners. CoRR Xuechen Li, Florian Tramèr, Percy Liang, Tatsunori Hashimoto
2021	—	`—`	Measuring and enhancing the security of machine learning. Florian Tramèr
2021	J	`jnl`	Membership Inference Attacks From First Principles. CoRR Nicholas Carlini, Steve Chien, Milad Nasr, Shuang Song, Andreas Terzis, Florian Tramèr
2021	J	`jnl`	NeuraCrypt is not private. CoRR Nicholas Carlini, Sanjam Garg, Somesh Jha, Saeed Mahloujifar, Mohammad Mahmoody, Florian Tramèr
2021	A*	`conf`	SquirRL: Automating Attack Analysis on Blockchain Incentive Mechanisms with Deep Reinforcement Learning. NDSS Charlie Hou, Mingxun Zhou, Yan Ji, Phil Daian, Florian Tramèr, Giulia Fanti, Ari Juels
2020	J	`jnl`	An Attack on InstaHide: Is Private Learning Possible with Instance Encoding? CoRR Nicholas Carlini, Samuel Deng, Sanjam Garg, Somesh Jha, Saeed Mahloujifar, Mohammad Mahmoody, Shuang Song, Abhradeep Thakurta, Florian Tramèr
2020	J	`jnl`	Differentially Private Learning Needs Better Features (or Much More Data). CoRR Florian Tramèr, Dan Boneh
2020	J	`jnl`	Extracting Training Data from Large Language Models. CoRR Nicholas Carlini, Florian Tramèr, Eric Wallace, Matthew Jagielski, Ariel Herbert-Voss, Katherine Lee, Adam Roberts, Tom B. Brown, Dawn Song, Úlfar Erlingsson, Alina Oprea, Colin Raffel
2020	A*	`conf`	Fundamental Tradeoffs between Invariance and Sensitivity to Adversarial Perturbations. ICML Florian Tramèr, Jens Behrmann, Nicholas Carlini, Nicolas Papernot, Jörn-Henrik Jacobsen
2020	J	`jnl`	Fundamental Tradeoffs between Invariance and Sensitivity to Adversarial Perturbations. CoRR Florian Tramèr, Jens Behrmann, Nicholas Carlini, Nicolas Papernot, Jörn-Henrik Jacobsen
2020	J	`jnl`	Label-Only Membership Inference Attacks. CoRR Christopher A. Choquette-Choo, Florian Tramèr, Nicholas Carlini, Nicolas Papernot
2020	A*	`conf`	On Adaptive Attacks to Adversarial Example Defenses. NeurIPS Florian Tramèr, Nicholas Carlini, Wieland Brendel, Aleksander Madry
2020	J	`jnl`	On Adaptive Attacks to Adversarial Example Defenses. CoRR Florian Tramèr, Nicholas Carlini, Wieland Brendel, Aleksander Madry
2020	A*	`conf`	Remote Side-Channel Attacks on Anonymous Transactions. USENIX Security Symposium Florian Tramèr, Dan Boneh, Kenny Paterson
2020	J	`jnl`	Remote Side-Channel Attacks on Anonymous Transactions. IACR Cryptol. ePrint Arch. Florian Tramèr, Dan Boneh, Kenneth G. Paterson
2020	—	`conf`	SentiNet: Detecting Localized Universal Attacks Against Deep Learning Systems. SP (Workshops) Edward Chou, Florian Tramèr, Giancarlo Pellegrino
2020	—	`conf`	Third International Workshop on Dependable and Secure Machine Learning - DSML 2020. DSN Workshops Homa Alemzadeh, Rakesh Bobba, Varun Chandrasekaran, David E. Evans, Nicolas Papernot, Karthik Pattabiraman, Florian Tramèr
2019	A*	`conf`	AdVersarial: Perceptual Ad Blocking meets Adversarial Machine Learning. CCS Florian Tramèr, Pascal Dupré, Gili Rusak, Giancarlo Pellegrino, Dan Boneh
2019	J	`jnl`	Advances and Open Problems in Federated Learning. CoRR Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Kallista A. Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D'Oliveira, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adrià Gascón, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaïd Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konecný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Mariana Raykova, Hang Qi, Daniel Ramage, Ramesh Raskar, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao
2019	A*	`conf`	Adversarial Training and Robustness for Multiple Perturbations. NeurIPS Florian Tramèr, Dan Boneh
2019	J	`jnl`	Adversarial Training and Robustness for Multiple Perturbations. CoRR Florian Tramèr, Dan Boneh
2019	J	`jnl`	Exploiting Excessive Invariance caused by Norm-Bounded Adversarial Robustness. CoRR Jörn-Henrik Jacobsen, Jens Behrmann, Nicholas Carlini, Florian Tramèr, Nicolas Papernot
2019	—	`conf`	Slalom: Fast, Verifiable and Private Execution of Neural Networks in Trusted Hardware. ICLR Florian Tramèr, Dan Boneh
2019	J	`jnl`	SquirRL: Automating Attack Discovery on Blockchain Incentive Mechanisms with Deep Reinforcement Learning. CoRR Charlie Hou, Mingxun Zhou, Yan Ji, Phil Daian, Florian Tramèr, Giulia Fanti, Ari Juels
2019	J	`jnl`	The Hydra Framework for Principled, Automated Bug Bounties. IEEE Secur. Priv. Lorenz Breidenbach, Philip Daian, Florian Tramèr, Ari Juels
2018	J	`jnl`	Ad-versarial: Defeating Perceptual Ad-Blocking. CoRR Florian Tramèr, Pascal Dupré, Gili Rusak, Giancarlo Pellegrino, Dan Boneh
2018	—	`conf`	Ensemble Adversarial Training: Attacks and Defenses. ICLR (Poster) Florian Tramèr, Alexey Kurakin, Nicolas Papernot, Ian J. Goodfellow, Dan Boneh, Patrick D. McDaniel
2018	A*	`conf`	Enter the Hydra: Towards Principled Bug Bounties and Exploit-Resistant Smart Contracts. USENIX Security Symposium Lorenz Breidenbach, Philip Daian, Florian Tramèr, Ari Juels
2018	—	`conf`	Physical Adversarial Examples for Object Detectors. WOOT @ USENIX Security Symposium Dawn Song, Kevin Eykholt, Ivan Evtimov, Earlence Fernandes, Bo Li, Amir Rahmati, Florian Tramèr, Atul Prakash, Tadayoshi Kohno
2018	J	`jnl`	Physical Adversarial Examples for Object Detectors. CoRR Kevin Eykholt, Ivan Evtimov, Earlence Fernandes, Bo Li, Amir Rahmati, Florian Tramèr, Atul Prakash, Tadayoshi Kohno, Dawn Song
2018	J	`jnl`	SentiNet: Detecting Physical Attacks Against Deep Learning Systems. CoRR Edward Chou, Florian Tramèr, Giancarlo Pellegrino, Dan Boneh
2018	J	`jnl`	Slalom: Fast, Verifiable and Private Execution of Neural Networks in Trusted Hardware. CoRR Florian Tramèr, Dan Boneh
2017	J	`jnl`	Addressing Beacon re-identification attacks: quantification and mitigation of privacy risks. J. Am. Medical Informatics Assoc. Jean Louis Raisaro, Florian Tramèr, Zhanglong Ji, Diyue Bu, Yongan Zhao, W. Knox Carey, David D. Lloyd, Heidi Sofia, Dixie Baker, Paul Flicek, Suyash S. Shringarpure, Carlos D. Bustamante, Shuang Wang, Xiaoqian Jiang, Lucila Ohno-Machado, Haixu Tang, Xiaofeng Wang, Jean-Pierre Hubaux
2017	J	`jnl`	Ensemble Adversarial Training: Attacks and Defenses. CoRR Florian Tramèr, Alexey Kurakin, Nicolas Papernot, Dan Boneh, Patrick D. McDaniel
2017	J	`jnl`	Enter the Hydra: Towards Principled Bug Bounties and Exploit-Resistant Smart Contracts. IACR Cryptol. ePrint Arch. Lorenz Breidenbach, Philip Daian, Florian Tramèr, Ari Juels
2017	A	`conf`	FairTest: Discovering Unwarranted Associations in Data-Driven Applications. EuroS&P Florian Tramèr, Vaggelis Atlidakis, Roxana Geambasu, Daniel J. Hsu, Jean-Pierre Hubaux, Mathias Humbert, Ari Juels, Huang Lin
2017	—	`conf`	Formal Abstractions for Attested Execution Secure Processors. EUROCRYPT (1) Rafael Pass, Elaine Shi, Florian Tramèr
2017	J	`jnl`	Note on Attacking Object Detectors with Adversarial Stickers. CoRR Kevin Eykholt, Ivan Evtimov, Earlence Fernandes, Bo Li, Dawn Song, Tadayoshi Kohno, Amir Rahmati, Atul Prakash, Florian Tramèr
2017	J	`jnl`	PrivateRide: A Privacy-Enhanced Ride-Hailing Service. Proc. Priv. Enhancing Technol. Anh Pham, Italo Dacosta, Bastien Jacot-Guillarmod, Kévin Huguenin, Taha Hajar, Florian Tramèr, Virgil D. Gligor, Jean-Pierre Hubaux
2017	A	`conf`	Sealed-Glass Proofs: Using Transparent Enclaves to Prove and Sell Knowledge. EuroS&P Florian Tramèr, Fan Zhang, Huang Lin, Jean-Pierre Hubaux, Ari Juels, Elaine Shi
2017	J	`jnl`	The Space of Transferable Adversarial Examples. CoRR Florian Tramèr, Nicolas Papernot, Ian J. Goodfellow, Dan Boneh, Patrick D. McDaniel
2016	J	`jnl`	Formal Abstractions for Attested Execution Secure Processors. IACR Cryptol. ePrint Arch. Rafael Pass, Elaine Shi, Florian Tramèr
2016	J	`jnl`	On solving L P N using B K W and variants - Implementation and analysis. Cryptogr. Commun. Sonia Bogos, Florian Tramèr, Serge Vaudenay
2016	J	`jnl`	Sealed-Glass Proofs: Using Transparent Enclaves to Prove and Sell Knowledge. IACR Cryptol. ePrint Arch. Florian Tramèr, Fan Zhang, Huang Lin, Jean-Pierre Hubaux, Ari Juels, Elaine Shi
2016	A*	`conf`	Stealing Machine Learning Models via Prediction APIs. USENIX Security Symposium Florian Tramèr, Fan Zhang, Ari Juels, Michael K. Reiter, Thomas Ristenpart
2016	J	`jnl`	Stealing Machine Learning Models via Prediction APIs. CoRR Florian Tramèr, Fan Zhang, Ari Juels, Michael K. Reiter, Thomas Ristenpart
2015	—	`conf`	Better Algorithms for LWE and LWR. EUROCRYPT (1) Alexandre Duc, Florian Tramèr, Serge Vaudenay
2015	J	`jnl`	Better Algorithms for LWE and LWR. IACR Cryptol. ePrint Arch. Alexandre Duc, Florian Tramèr, Serge Vaudenay
2015	A*	`conf`	Differential Privacy with Bounded Priors: Reconciling Utility and Privacy in Genome-Wide Association Studies. CCS Florian Tramèr, Zhicong Huang, Jean-Pierre Hubaux, Erman Ayday
2015	J	`jnl`	Discovering Unwarranted Associations in Data-Driven Applications with the FairTest Testing Toolkit. CoRR Florian Tramèr, Vaggelis Atlidakis, Roxana Geambasu, Daniel J. Hsu, Jean-Pierre Hubaux, Mathias Humbert, Ari Juels, Huang Lin
2015	J	`jnl`	On Solving Lpn using BKW and Variants. IACR Cryptol. ePrint Arch. Sonia Bogos, Florian Tramèr, Serge Vaudenay