Securing AI Agents with Information-Flow Control
Manuel Costa, Boris Köpf, Aashish Kolluri, Andrew Paverd, Mark Russinovich, Ahmed Salem, Shruti Tople, Lukas Wutschitz, Santiago Zanella-Béguelin
May 2025
Shruti Tople
Chercheur principal
Papiers de Collaboration
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The Canary’s Echo: Auditing Privacy Risks of LLM-Generated Synthetic Text
Matthieu Meeus, Lukas Wutschitz, Santiago Zanella-Béguelin, Reza Shokri, Shruti Tople
February 2025
-
The Canary’s Echo: Auditing Privacy Risks of LLM-Generated Synthetic Text
Matthieu Meeus, Lukas Wutschitz, Santiago Zanella-Béguelin, Shruti Tople, Reza Shokri
ICML 2025 | February 2025
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-
-
Permissive Information-Flow Analysis for Large Language Models
Shoaib Ahmed Siddiqui, Radhika Gaonkar, Boris Köpf, David Krueger, Andrew Paverd, Ahmed Salem, Shruti Tople, Lukas Wutschitz, Menglin Xia, Santiago Zanella-Béguelin
October 2024
-
Closed-Form Bounds for DP-SGD against Record-level Inference
Giovanni Cherubin, Boris Köpf, Andrew Paverd, Shruti Tople, Lukas Wutschitz, Santiago Zanella-Béguelin
USENIX Security Symposium | August 2024
-
Investigating the Effect of Misalignment on Membership Privacy in the White-box Setting
Ana-Maria Cretu, Daniel Jones, Yves-Alexandre de Montjoye, Shruti Tople
Proceedings on Privacy Enhancing Technologies 2024 | June 2024
-
Invariant Aggregator for Defending against Federated Backdoor Attacks
Xiaoya Wang, Dimitrios Dimitriadis, Oluwasanmi Koyejo, Shruti Tople
International Conference on Artificial Intelligence and Statistics, AISTATS | May 2024
Rédacteur(s) en chef: Sanjoy Dasgupta, Stephan Mandt, Yingzhen Li
-
-
-
On the Efficacy of Differentially Private Few-shot Image Classification
Marlon Tobaben, Aliaksandra Shysheya, John Bronskill, Andrew Paverd, Shruti Tople, Santiago Zanella-Béguelin, Richard Turner, Antti Honkela
Transactions on Machine Learning Research | December 2023, Vol 2023
-
Bayesian Estimation of Differential Privacy
Santiago Zanella-Béguelin, Lukas Wutschitz, Shruti Tople, Ahmed Salem, Victor Ruehle, Andrew Paverd, Mohammad Naseri, Boris Köpf, Daniel Jones
2023 International Conference on Machine Learning | July 2023
Rédacteur(s) en chef: Barbara Engelhardt, Emma Brunskill, Kyunghyun Cho
-
Analyzing Leakage of Personally Identifiable Information in Language Models
Nils Lukas, Ahmed Salem, Robert Sim, Shruti Tople, Lukas Wutschitz, Santiago Zanella-Béguelin
2023 IEEE Symposium on Security and Privacy | May 2023
-
SoK: Let the Privacy Games Begin! A Unified Treatment of Data Inference Privacy in Machine Learning
Ahmed Salem, Giovanni Cherubin, David Evans, Boris Köpf, Andrew Paverd, Anshuman Suri, Shruti Tople, Santiago Zanella-Béguelin
2023 IEEE Symposium on Security and Privacy | May 2023
-
Distribution Inference Risks: Identifying and Mitigating Sources of Leakage
Valentin Hartmann, Leo Meynent, Maxime Peyrard, Dimitrios Dimitriadis, Shruti Tople, Robert West
IEEE Conference on Secure and Trustworthy Machine Learning (SatML) | February 2023
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-
-
Membership Inference Attacks and Generalization: A Causal Perspective
Teodora Baluta, Shiqi Shen, S. Hitarth, Shruti Tople, Prateek Saxena
Computer and Communications Security (CCS) | November 2022
-
MACE: A Flexible Framework for Membership Privacy Estimation in Generative Models
Yixi Xu, Sumit Mukherjee, Xiyang Liu, Shruti Tople, Rahul Dodhia, Juan M. Lavista Ferres
Transactions on Machine Learning Research (TMLR) | October 2022
-
-
-
Leakage of Dataset Properties in Multi-Party Machine Learning
Wanrong Zhang, Shruti Tople, Olga Ohrimenko
Usenix Security | August 2021
-
Domain Generalization using Causal Matching
Divyat Mahajan, Shruti Tople, Amit Sharma
International Conference on Machine Learning (ICML) | July 2021
-
Grey-box Extraction of Natural Language Models
Santiago Zanella-Béguelin, Shruti Tople, Andrew Paverd, Boris Köpf
International Conference on Machine Learning | July 2021
Rédacteur(s) en chef: Marina Meila and Tong Zhang
-
Falcon: Honest-Majority Maliciously Secure Framework for Private Deep Learning
Sameer Wagh, Shruti Tople, Fabrice Benhamouda, Eyal Kushilevitz, Prateek Mittal, Tal Rabin
Privacy Enhancing Technologies Symposium (PETS) | June 2021
-
Causally Constrained Data Synthesis for Private Data Release
Varun Chandrasekaran, Darren Edge, Somesh Jha, Amit Sharma, Cheng Zhang, Shruti Tople
Distributed and Private Machine Learning (DPML) Workshop at ICLR'21 | May 2021
-
-
-
The Connection between Out-of-Distribution Generalization and Privacy of ML Models
Divyat Mahajan, Shruti Tople, Amit Sharma
Privacy Preserving Machine Learning (PriML/PPML) Workshop at NeurIPS'20 | December 2020
-
Analyzing Information Leakage of Updates to Natural Language Models
Santiago Zanella-Béguelin, Lukas Wutschitz, Shruti Tople, Victor Ruehle, Andrew Paverd, Olga Ohrimenko, Boris Köpf, Marc Brockschmidt
ACM Conference on Computer and Communication Security (CCS) | November 2020
-
An Empirical Study on the Intrinsic Privacy of SGD
Stephanie Hyland, Shruti Tople
Theory and Practice of Differential Privacy (CCS Worshop) | November 2020
-
Robust P2P Primitives Using SGX Enclaves
Yaoqi Jia, Shruti Tople, Tarik Moataz, Deli Gong, Prateek Saxena, Zhenkai Liang
23rd International Symposium on Research in Attacks, Intrusions and Defenses (RAID) | October 2020
-
Alleviating Privacy Attacks via Causal Learning
Shruti Tople, Amit Sharma, Aditya V. Nori
International Conference on Machine Learning (ICML) | July 2020
-
-
-
Collaborative Machine Learning Markets
Olga Ohrimenko, Shruti Tople , Sebastian Tschiatschek
Smooth Games Optimization (NeurIPS Workshop) | December 2019
-
PRO-ORAM: Practical Read-Only Oblivious RAM
Shruti Tople, Yaoqi Jia, Prateek Saxena
22nd International Symposium on Research in Attacks, Intrusions and Defenses (RAID) | September 2019
-
-
-
Privado: Practical and Secure DNN Inference with Enclaves
Karan Grover, Shruti Tople, Shweta Shinde, Ranjita Bhagwan, Ramachandran Ramjee
September 2018
-
VeriCount: Verifiable Resource Accounting Using Hardware and Software Isolation
Shruti Tople , Soyeon Park, Min Suk Kang, Prateek Saxena
Applied Cryptography and Network Security (ACNS) | July 2018
-
-
-
A Traceability Analysis of Monero’s Blockchain
Amrit Kumar, Clement Fischer, Shruti Tople, Prateek Saxena
European Symposium on Research in Computer Security (ESORICS) | September 2017
-
On the Trade-Offs in Oblivious Execution Techniques
Shruti Tople , Prateek Saxena
Detection of Intrusions and Malware & Vulnerability Assessment (DIMVA) | July 2017
-
Panoply: Low-TCB Linux Applications With SGX Enclaves
Shweta Shinde, Dat Le Tien, Shruti Tople , Prateek Saxena
Network and Distributed System Security Symposium (NDSS) | March 2017
-
-
-
AUROR: Defending Against Poisoning Attacks in Collaborative Deep Learning Systems
Shiqi Shen, Shruti Tople, Prateek Saxena
Annual Computer Security Applications Conference (ACSAC) | December 2016
-
OblivP2P: An Oblivious Peer-to-Peer Content Sharing System
Yaoqi Jia, Tarik Moataz, Shruti Tople
USENIX Security Symposium | August 2016
-
-
-
AUTOCRYPT: Enabling Homomorphic Computation on Servers to Protect Sensitive Web Content
Shruti Tople, Shweta Shinde, Zhaofeng Chen, Prateek Saxena
Computer and Communications Security (CCS 2013) | November 2013
-
Protecting Sensitive Web Content from Client-side Vulnerabilities with CRYPTONs
Xinshu Dong, Zhaofeng Chen, Hossein Siaditi, Shruti Tople, Prateek Saxena, Zhenkai Liang
Computer and Communications Security (CCS 2013) | November 2013
-
-
-
Securing AI Agents with Information-Flow Control
Manuel Costa, Boris Köpf, Aashish Kolluri, Andrew Paverd, Mark Russinovich, Ahmed Salem, Shruti Tople, Lukas Wutschitz, Santiago Zanella-Béguelin
May 2025
-
The Canary’s Echo: Auditing Privacy Risks of LLM-Generated Synthetic Text
Matthieu Meeus, Lukas Wutschitz, Santiago Zanella-Béguelin, Reza Shokri, Shruti Tople
February 2025
-
The Canary’s Echo: Auditing Privacy Risks of LLM-Generated Synthetic Text
Matthieu Meeus, Lukas Wutschitz, Santiago Zanella-Béguelin, Shruti Tople, Reza Shokri
ICML 2025 | February 2025
-
Permissive Information-Flow Analysis for Large Language Models
Shoaib Ahmed Siddiqui, Radhika Gaonkar, Boris Köpf, David Krueger, Andrew Paverd, Ahmed Salem, Shruti Tople, Lukas Wutschitz, Menglin Xia, Santiago Zanella-Béguelin
October 2024
-
Closed-Form Bounds for DP-SGD against Record-level Inference
Giovanni Cherubin, Boris Köpf, Andrew Paverd, Shruti Tople, Lukas Wutschitz, Santiago Zanella-Béguelin
USENIX Security Symposium | August 2024
-
Investigating the Effect of Misalignment on Membership Privacy in the White-box Setting
Ana-Maria Cretu, Daniel Jones, Yves-Alexandre de Montjoye, Shruti Tople
Proceedings on Privacy Enhancing Technologies 2024 | June 2024
-
Invariant Aggregator for Defending against Federated Backdoor Attacks
Xiaoya Wang, Dimitrios Dimitriadis, Oluwasanmi Koyejo, Shruti Tople
International Conference on Artificial Intelligence and Statistics, AISTATS | May 2024
Rédacteur(s) en chef: Sanjoy Dasgupta, Stephan Mandt, Yingzhen Li
-
On the Efficacy of Differentially Private Few-shot Image Classification
Marlon Tobaben, Aliaksandra Shysheya, John Bronskill, Andrew Paverd, Shruti Tople, Santiago Zanella-Béguelin, Richard Turner, Antti Honkela
Transactions on Machine Learning Research | December 2023, Vol 2023
-
Bayesian Estimation of Differential Privacy
Santiago Zanella-Béguelin, Lukas Wutschitz, Shruti Tople, Ahmed Salem, Victor Ruehle, Andrew Paverd, Mohammad Naseri, Boris Köpf, Daniel Jones
2023 International Conference on Machine Learning | July 2023
Rédacteur(s) en chef: Barbara Engelhardt, Emma Brunskill, Kyunghyun Cho
-
Analyzing Leakage of Personally Identifiable Information in Language Models
Nils Lukas, Ahmed Salem, Robert Sim, Shruti Tople, Lukas Wutschitz, Santiago Zanella-Béguelin
2023 IEEE Symposium on Security and Privacy | May 2023
-
SoK: Let the Privacy Games Begin! A Unified Treatment of Data Inference Privacy in Machine Learning
Ahmed Salem, Giovanni Cherubin, David Evans, Boris Köpf, Andrew Paverd, Anshuman Suri, Shruti Tople, Santiago Zanella-Béguelin
2023 IEEE Symposium on Security and Privacy | May 2023
-
Distribution Inference Risks: Identifying and Mitigating Sources of Leakage
Valentin Hartmann, Leo Meynent, Maxime Peyrard, Dimitrios Dimitriadis, Shruti Tople, Robert West
IEEE Conference on Secure and Trustworthy Machine Learning (SatML) | February 2023
-
Membership Inference Attacks and Generalization: A Causal Perspective
Teodora Baluta, Shiqi Shen, S. Hitarth, Shruti Tople, Prateek Saxena
Computer and Communications Security (CCS) | November 2022
-
MACE: A Flexible Framework for Membership Privacy Estimation in Generative Models
Yixi Xu, Sumit Mukherjee, Xiyang Liu, Shruti Tople, Rahul Dodhia, Juan M. Lavista Ferres
Transactions on Machine Learning Research (TMLR) | October 2022
-
Leakage of Dataset Properties in Multi-Party Machine Learning
Wanrong Zhang, Shruti Tople, Olga Ohrimenko
Usenix Security | August 2021
-
Domain Generalization using Causal Matching
Divyat Mahajan, Shruti Tople, Amit Sharma
International Conference on Machine Learning (ICML) | July 2021
-
Grey-box Extraction of Natural Language Models
Santiago Zanella-Béguelin, Shruti Tople, Andrew Paverd, Boris Köpf
International Conference on Machine Learning | July 2021
Rédacteur(s) en chef: Marina Meila and Tong Zhang
-
Causally Constrained Data Synthesis for Private Data Release
Varun Chandrasekaran, Darren Edge, Somesh Jha, Amit Sharma, Cheng Zhang, Shruti Tople
Distributed and Private Machine Learning (DPML) Workshop at ICLR'21 | May 2021
-
The Connection between Out-of-Distribution Generalization and Privacy of ML Models
Divyat Mahajan, Shruti Tople, Amit Sharma
Privacy Preserving Machine Learning (PriML/PPML) Workshop at NeurIPS'20 | December 2020
-
Analyzing Information Leakage of Updates to Natural Language Models
Santiago Zanella-Béguelin, Lukas Wutschitz, Shruti Tople, Victor Ruehle, Andrew Paverd, Olga Ohrimenko, Boris Köpf, Marc Brockschmidt
ACM Conference on Computer and Communication Security (CCS) | November 2020
-
Alleviating Privacy Attacks via Causal Learning
Shruti Tople, Amit Sharma, Aditya V. Nori
International Conference on Machine Learning (ICML) | July 2020
-
Collaborative Machine Learning Markets
Olga Ohrimenko, Shruti Tople , Sebastian Tschiatschek
Smooth Games Optimization (NeurIPS Workshop) | December 2019
-
-
-
Securing AI Agents with Information-Flow Control
Manuel Costa, Boris Köpf, Aashish Kolluri, Andrew Paverd, Mark Russinovich, Ahmed Salem, Shruti Tople, Lukas Wutschitz, Santiago Zanella-Béguelin
May 2025
-
The Canary’s Echo: Auditing Privacy Risks of LLM-Generated Synthetic Text
Matthieu Meeus, Lukas Wutschitz, Santiago Zanella-Béguelin, Reza Shokri, Shruti Tople
February 2025
-
Permissive Information-Flow Analysis for Large Language Models
Shoaib Ahmed Siddiqui, Radhika Gaonkar, Boris Köpf, David Krueger, Andrew Paverd, Ahmed Salem, Shruti Tople, Lukas Wutschitz, Menglin Xia, Santiago Zanella-Béguelin
October 2024
-
Closed-Form Bounds for DP-SGD against Record-level Inference
Giovanni Cherubin, Boris Köpf, Andrew Paverd, Shruti Tople, Lukas Wutschitz, Santiago Zanella-Béguelin
USENIX Security Symposium | August 2024
-
Investigating the Effect of Misalignment on Membership Privacy in the White-box Setting
Ana-Maria Cretu, Daniel Jones, Yves-Alexandre de Montjoye, Shruti Tople
Proceedings on Privacy Enhancing Technologies 2024 | June 2024
-
Invariant Aggregator for Defending against Federated Backdoor Attacks
Xiaoya Wang, Dimitrios Dimitriadis, Oluwasanmi Koyejo, Shruti Tople
International Conference on Artificial Intelligence and Statistics, AISTATS | May 2024
Rédacteur(s) en chef: Sanjoy Dasgupta, Stephan Mandt, Yingzhen Li
-
On the Efficacy of Differentially Private Few-shot Image Classification
Marlon Tobaben, Aliaksandra Shysheya, John Bronskill, Andrew Paverd, Shruti Tople, Santiago Zanella-Béguelin, Richard Turner, Antti Honkela
Transactions on Machine Learning Research | December 2023, Vol 2023
-
Bayesian Estimation of Differential Privacy
Santiago Zanella-Béguelin, Lukas Wutschitz, Shruti Tople, Ahmed Salem, Victor Ruehle, Andrew Paverd, Mohammad Naseri, Boris Köpf, Daniel Jones
2023 International Conference on Machine Learning | July 2023
Rédacteur(s) en chef: Barbara Engelhardt, Emma Brunskill, Kyunghyun Cho
-
Analyzing Leakage of Personally Identifiable Information in Language Models
Nils Lukas, Ahmed Salem, Robert Sim, Shruti Tople, Lukas Wutschitz, Santiago Zanella-Béguelin
2023 IEEE Symposium on Security and Privacy | May 2023
-
SoK: Let the Privacy Games Begin! A Unified Treatment of Data Inference Privacy in Machine Learning
Ahmed Salem, Giovanni Cherubin, David Evans, Boris Köpf, Andrew Paverd, Anshuman Suri, Shruti Tople, Santiago Zanella-Béguelin
2023 IEEE Symposium on Security and Privacy | May 2023
-
Distribution Inference Risks: Identifying and Mitigating Sources of Leakage
Valentin Hartmann, Leo Meynent, Maxime Peyrard, Dimitrios Dimitriadis, Shruti Tople, Robert West
IEEE Conference on Secure and Trustworthy Machine Learning (SatML) | February 2023
-
Membership Inference Attacks and Generalization: A Causal Perspective
Teodora Baluta, Shiqi Shen, S. Hitarth, Shruti Tople, Prateek Saxena
Computer and Communications Security (CCS) | November 2022
-
MACE: A Flexible Framework for Membership Privacy Estimation in Generative Models
Yixi Xu, Sumit Mukherjee, Xiyang Liu, Shruti Tople, Rahul Dodhia, Juan M. Lavista Ferres
Transactions on Machine Learning Research (TMLR) | October 2022
-
Leakage of Dataset Properties in Multi-Party Machine Learning
Wanrong Zhang, Shruti Tople, Olga Ohrimenko
Usenix Security | August 2021
-
Grey-box Extraction of Natural Language Models
Santiago Zanella-Béguelin, Shruti Tople, Andrew Paverd, Boris Köpf
International Conference on Machine Learning | July 2021
Rédacteur(s) en chef: Marina Meila and Tong Zhang
-
Falcon: Honest-Majority Maliciously Secure Framework for Private Deep Learning
Sameer Wagh, Shruti Tople, Fabrice Benhamouda, Eyal Kushilevitz, Prateek Mittal, Tal Rabin
Privacy Enhancing Technologies Symposium (PETS) | June 2021
-
Causally Constrained Data Synthesis for Private Data Release
Varun Chandrasekaran, Darren Edge, Somesh Jha, Amit Sharma, Cheng Zhang, Shruti Tople
Distributed and Private Machine Learning (DPML) Workshop at ICLR'21 | May 2021
-
The Connection between Out-of-Distribution Generalization and Privacy of ML Models
Divyat Mahajan, Shruti Tople, Amit Sharma
Privacy Preserving Machine Learning (PriML/PPML) Workshop at NeurIPS'20 | December 2020
-
Analyzing Information Leakage of Updates to Natural Language Models
Santiago Zanella-Béguelin, Lukas Wutschitz, Shruti Tople, Victor Ruehle, Andrew Paverd, Olga Ohrimenko, Boris Köpf, Marc Brockschmidt
ACM Conference on Computer and Communication Security (CCS) | November 2020
-
An Empirical Study on the Intrinsic Privacy of SGD
Stephanie Hyland, Shruti Tople
Theory and Practice of Differential Privacy (CCS Worshop) | November 2020
-
Robust P2P Primitives Using SGX Enclaves
Yaoqi Jia, Shruti Tople, Tarik Moataz, Deli Gong, Prateek Saxena, Zhenkai Liang
23rd International Symposium on Research in Attacks, Intrusions and Defenses (RAID) | October 2020
-
Alleviating Privacy Attacks via Causal Learning
Shruti Tople, Amit Sharma, Aditya V. Nori
International Conference on Machine Learning (ICML) | July 2020
-
Collaborative Machine Learning Markets
Olga Ohrimenko, Shruti Tople , Sebastian Tschiatschek
Smooth Games Optimization (NeurIPS Workshop) | December 2019
-
PRO-ORAM: Practical Read-Only Oblivious RAM
Shruti Tople, Yaoqi Jia, Prateek Saxena
22nd International Symposium on Research in Attacks, Intrusions and Defenses (RAID) | September 2019
-
Privado: Practical and Secure DNN Inference with Enclaves
Karan Grover, Shruti Tople, Shweta Shinde, Ranjita Bhagwan, Ramachandran Ramjee
September 2018
-
VeriCount: Verifiable Resource Accounting Using Hardware and Software Isolation
Shruti Tople , Soyeon Park, Min Suk Kang, Prateek Saxena
Applied Cryptography and Network Security (ACNS) | July 2018
-
A Traceability Analysis of Monero’s Blockchain
Amrit Kumar, Clement Fischer, Shruti Tople, Prateek Saxena
European Symposium on Research in Computer Security (ESORICS) | September 2017
-
On the Trade-Offs in Oblivious Execution Techniques
Shruti Tople , Prateek Saxena
Detection of Intrusions and Malware & Vulnerability Assessment (DIMVA) | July 2017
-
Panoply: Low-TCB Linux Applications With SGX Enclaves
Shweta Shinde, Dat Le Tien, Shruti Tople , Prateek Saxena
Network and Distributed System Security Symposium (NDSS) | March 2017
-
AUROR: Defending Against Poisoning Attacks in Collaborative Deep Learning Systems
Shiqi Shen, Shruti Tople, Prateek Saxena
Annual Computer Security Applications Conference (ACSAC) | December 2016
-
OblivP2P: An Oblivious Peer-to-Peer Content Sharing System
Yaoqi Jia, Tarik Moataz, Shruti Tople
USENIX Security Symposium | August 2016
-
AUTOCRYPT: Enabling Homomorphic Computation on Servers to Protect Sensitive Web Content
Shruti Tople, Shweta Shinde, Zhaofeng Chen, Prateek Saxena
Computer and Communications Security (CCS 2013) | November 2013
-
Protecting Sensitive Web Content from Client-side Vulnerabilities with CRYPTONs
Xinshu Dong, Zhaofeng Chen, Hossein Siaditi, Shruti Tople, Prateek Saxena, Zhenkai Liang
Computer and Communications Security (CCS 2013) | November 2013
-
-
-
Domain Generalization using Causal Matching
Divyat Mahajan, Shruti Tople, Amit Sharma
International Conference on Machine Learning (ICML) | July 2021
-
-
-
Robust P2P Primitives Using SGX Enclaves
Yaoqi Jia, Shruti Tople, Tarik Moataz, Deli Gong, Prateek Saxena, Zhenkai Liang
23rd International Symposium on Research in Attacks, Intrusions and Defenses (RAID) | October 2020
-
Privado: Practical and Secure DNN Inference with Enclaves
Karan Grover, Shruti Tople, Shweta Shinde, Ranjita Bhagwan, Ramachandran Ramjee
September 2018
-
-
-
Collaborative Machine Learning Markets
Olga Ohrimenko, Shruti Tople , Sebastian Tschiatschek
Smooth Games Optimization (NeurIPS Workshop) | December 2019
-
-
-
Securing AI Agents with Information-Flow Control
Manuel Costa, Boris Köpf, Aashish Kolluri, Andrew Paverd, Mark Russinovich, Ahmed Salem, Shruti Tople, Lukas Wutschitz, Santiago Zanella-Béguelin
May 2025
-
Permissive Information-Flow Analysis for Large Language Models
Shoaib Ahmed Siddiqui, Radhika Gaonkar, Boris Köpf, David Krueger, Andrew Paverd, Ahmed Salem, Shruti Tople, Lukas Wutschitz, Menglin Xia, Santiago Zanella-Béguelin
October 2024
-
-
-
The Canary’s Echo: Auditing Privacy Risks of LLM-Generated Synthetic Text
Matthieu Meeus, Lukas Wutschitz, Santiago Zanella-Béguelin, Shruti Tople, Reza Shokri
ICML 2025 | February 2025
-
Closed-Form Bounds for DP-SGD against Record-level Inference
Giovanni Cherubin, Boris Köpf, Andrew Paverd, Shruti Tople, Lukas Wutschitz, Santiago Zanella-Béguelin
USENIX Security Symposium | August 2024
-
Investigating the Effect of Misalignment on Membership Privacy in the White-box Setting
Ana-Maria Cretu, Daniel Jones, Yves-Alexandre de Montjoye, Shruti Tople
Proceedings on Privacy Enhancing Technologies 2024 | June 2024
-
Invariant Aggregator for Defending against Federated Backdoor Attacks
Xiaoya Wang, Dimitrios Dimitriadis, Oluwasanmi Koyejo, Shruti Tople
International Conference on Artificial Intelligence and Statistics, AISTATS | May 2024
Rédacteur(s) en chef: Sanjoy Dasgupta, Stephan Mandt, Yingzhen Li
-
Bayesian Estimation of Differential Privacy
Santiago Zanella-Béguelin, Lukas Wutschitz, Shruti Tople, Ahmed Salem, Victor Ruehle, Andrew Paverd, Mohammad Naseri, Boris Köpf, Daniel Jones
2023 International Conference on Machine Learning | July 2023
Rédacteur(s) en chef: Barbara Engelhardt, Emma Brunskill, Kyunghyun Cho
-
Analyzing Leakage of Personally Identifiable Information in Language Models
Nils Lukas, Ahmed Salem, Robert Sim, Shruti Tople, Lukas Wutschitz, Santiago Zanella-Béguelin
2023 IEEE Symposium on Security and Privacy | May 2023
-
SoK: Let the Privacy Games Begin! A Unified Treatment of Data Inference Privacy in Machine Learning
Ahmed Salem, Giovanni Cherubin, David Evans, Boris Köpf, Andrew Paverd, Anshuman Suri, Shruti Tople, Santiago Zanella-Béguelin
2023 IEEE Symposium on Security and Privacy | May 2023
-
Distribution Inference Risks: Identifying and Mitigating Sources of Leakage
Valentin Hartmann, Leo Meynent, Maxime Peyrard, Dimitrios Dimitriadis, Shruti Tople, Robert West
IEEE Conference on Secure and Trustworthy Machine Learning (SatML) | February 2023
-
Membership Inference Attacks and Generalization: A Causal Perspective
Teodora Baluta, Shiqi Shen, S. Hitarth, Shruti Tople, Prateek Saxena
Computer and Communications Security (CCS) | November 2022
-
Leakage of Dataset Properties in Multi-Party Machine Learning
Wanrong Zhang, Shruti Tople, Olga Ohrimenko
Usenix Security | August 2021
-
Domain Generalization using Causal Matching
Divyat Mahajan, Shruti Tople, Amit Sharma
International Conference on Machine Learning (ICML) | July 2021
-
Grey-box Extraction of Natural Language Models
Santiago Zanella-Béguelin, Shruti Tople, Andrew Paverd, Boris Köpf
International Conference on Machine Learning | July 2021
Rédacteur(s) en chef: Marina Meila and Tong Zhang
-
Falcon: Honest-Majority Maliciously Secure Framework for Private Deep Learning
Sameer Wagh, Shruti Tople, Fabrice Benhamouda, Eyal Kushilevitz, Prateek Mittal, Tal Rabin
Privacy Enhancing Technologies Symposium (PETS) | June 2021
-
Causally Constrained Data Synthesis for Private Data Release
Varun Chandrasekaran, Darren Edge, Somesh Jha, Amit Sharma, Cheng Zhang, Shruti Tople
Distributed and Private Machine Learning (DPML) Workshop at ICLR'21 | May 2021
-
The Connection between Out-of-Distribution Generalization and Privacy of ML Models
Divyat Mahajan, Shruti Tople, Amit Sharma
Privacy Preserving Machine Learning (PriML/PPML) Workshop at NeurIPS'20 | December 2020
-
Analyzing Information Leakage of Updates to Natural Language Models
Santiago Zanella-Béguelin, Lukas Wutschitz, Shruti Tople, Victor Ruehle, Andrew Paverd, Olga Ohrimenko, Boris Köpf, Marc Brockschmidt
ACM Conference on Computer and Communication Security (CCS) | November 2020
-
An Empirical Study on the Intrinsic Privacy of SGD
Stephanie Hyland, Shruti Tople
Theory and Practice of Differential Privacy (CCS Worshop) | November 2020
-
Robust P2P Primitives Using SGX Enclaves
Yaoqi Jia, Shruti Tople, Tarik Moataz, Deli Gong, Prateek Saxena, Zhenkai Liang
23rd International Symposium on Research in Attacks, Intrusions and Defenses (RAID) | October 2020
-
Alleviating Privacy Attacks via Causal Learning
Shruti Tople, Amit Sharma, Aditya V. Nori
International Conference on Machine Learning (ICML) | July 2020
-
Collaborative Machine Learning Markets
Olga Ohrimenko, Shruti Tople , Sebastian Tschiatschek
Smooth Games Optimization (NeurIPS Workshop) | December 2019
-
PRO-ORAM: Practical Read-Only Oblivious RAM
Shruti Tople, Yaoqi Jia, Prateek Saxena
22nd International Symposium on Research in Attacks, Intrusions and Defenses (RAID) | September 2019
-
VeriCount: Verifiable Resource Accounting Using Hardware and Software Isolation
Shruti Tople , Soyeon Park, Min Suk Kang, Prateek Saxena
Applied Cryptography and Network Security (ACNS) | July 2018
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A Traceability Analysis of Monero’s Blockchain
Amrit Kumar, Clement Fischer, Shruti Tople, Prateek Saxena
European Symposium on Research in Computer Security (ESORICS) | September 2017
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On the Trade-Offs in Oblivious Execution Techniques
Shruti Tople , Prateek Saxena
Detection of Intrusions and Malware & Vulnerability Assessment (DIMVA) | July 2017
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Panoply: Low-TCB Linux Applications With SGX Enclaves
Shweta Shinde, Dat Le Tien, Shruti Tople , Prateek Saxena
Network and Distributed System Security Symposium (NDSS) | March 2017
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AUROR: Defending Against Poisoning Attacks in Collaborative Deep Learning Systems
Shiqi Shen, Shruti Tople, Prateek Saxena
Annual Computer Security Applications Conference (ACSAC) | December 2016
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OblivP2P: An Oblivious Peer-to-Peer Content Sharing System
Yaoqi Jia, Tarik Moataz, Shruti Tople
USENIX Security Symposium | August 2016
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AUTOCRYPT: Enabling Homomorphic Computation on Servers to Protect Sensitive Web Content
Shruti Tople, Shweta Shinde, Zhaofeng Chen, Prateek Saxena
Computer and Communications Security (CCS 2013) | November 2013
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Protecting Sensitive Web Content from Client-side Vulnerabilities with CRYPTONs
Xinshu Dong, Zhaofeng Chen, Hossein Siaditi, Shruti Tople, Prateek Saxena, Zhenkai Liang
Computer and Communications Security (CCS 2013) | November 2013
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The Canary’s Echo: Auditing Privacy Risks of LLM-Generated Synthetic Text
Matthieu Meeus, Lukas Wutschitz, Santiago Zanella-Béguelin, Reza Shokri, Shruti Tople
February 2025
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Privado: Practical and Secure DNN Inference with Enclaves
Karan Grover, Shruti Tople, Shweta Shinde, Ranjita Bhagwan, Ramachandran Ramjee
September 2018
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On the Efficacy of Differentially Private Few-shot Image Classification
Marlon Tobaben, Aliaksandra Shysheya, John Bronskill, Andrew Paverd, Shruti Tople, Santiago Zanella-Béguelin, Richard Turner, Antti Honkela
Transactions on Machine Learning Research | December 2023, Vol 2023
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MACE: A Flexible Framework for Membership Privacy Estimation in Generative Models
Yixi Xu, Sumit Mukherjee, Xiyang Liu, Shruti Tople, Rahul Dodhia, Juan M. Lavista Ferres
Transactions on Machine Learning Research (TMLR) | October 2022
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