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
Shruti Tople
Principal Researcher
Papiers de Collaboration
Publications par année
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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
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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
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
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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
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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
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
Filtre par zone de recherche
-
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
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
-
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
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
Publication Type
-
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
Privado: Practical and Secure DNN Inference with Enclaves
Karan Grover, Shruti Tople, Shweta Shinde, Ranjita Bhagwan, Ramachandran Ramjee
September 2018
-
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
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
-
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
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