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
Confidential Computing
Confidential AI
출판물
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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
-
Dataset and Lessons Learned from the 2024 SaTML LLM Capture-the-Flag Competition
Edoardo Debenedetti, Javier Rando, Daniel Paleka, Fineas Silaghi, Dragos Albastroiu, Niv Cohen, Yuval Lemberg, Reshmi Ghosh, Ahmed Salem, Rui Wen, Giovanni Cherubin, Santiago Zanella-Béguelin, Robin Schmid, Victor Klemm, Takahiro Miki, Chenhao Li, Stefan Kraft, Mario Fritz, Florian Tramer, Sahar Abdelnabi, Lea Schönherr
NeurIPS 2024 | June 2024
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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
편집자: 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, 제 2023 권
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Confidential Computing within an AI Accelerator
Kapil Vaswani, Stavros Volos, Cédric Fournet, Antonio Nino Diaz, Ken Gordon, Balaji Vembu, Sam Webster, David Chisnall, Saurabh Kulkarni, Graham Cunningham , Richard Osborne , Daniel Wilkinson
2023 USENIX Annual Technical Conference | July 2023
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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
편집자: Barbara Engelhardt, Emma Brunskill, Kyunghyun Cho
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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
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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
편집자: Marina Meila and Tong Zhang
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-
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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
-
Visor: Privacy-Preserving Video Analytics as a Cloud Service
Rishabh Poddar, Ganesh Ananthanarayanan, Srinath Setty, Stavros Volos, Raluca Ada Popa
29th USENIX Security Symposium | August 2020
CSAW 2020 Applied Research Competition Award (Runner-up)
-
Alleviating Privacy Attacks via Causal Learning
Shruti Tople, Amit Sharma, Aditya V. Nori
International Conference on Machine Learning (ICML) | July 2020
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-
-
An Algorithmic Framework For Differentially Private Data Analysis on Trusted Processors
Joshua Allen, Bolin Ding, Janardhan (Jana) Kulkarni, Harsha Nori, Olga Ohrimenko, Sergey Yekhanin
NeurIPS 2019 | August 2019
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-
-
Contamination Attacks and Mitigation in Multi-Party Machine Learning
Jamie Hayes, Olya Ohrimenko
Neural Information Processing Systems (NeurIPS) | December 2018
-
Graviton: Trusted Execution Environments on GPUs
Stavros Volos, Kapil Vaswani, Rordigo Bruno
13th USENIX Symposium on Operating Systems Design and Implementation | October 2018
-
-
-
Oblivious Multi-Party Machine Learning on Trusted Processors
Olya Ohrimenko, Felix Schuster, Cédric Fournet, Aastha Mehta, Sebastian Nowozin, Kapil Vaswani, Manuel Costa
The 25th USENIX Security Symposium 2016 | July 2016
-
-
-
Observing and Preventing Leakage in MapReduce
Olya Ohrimenko, Manuel Costa, Cédric Fournet, Christos Gkantsidis, Markulf Kohlweiss, Divya Sharma
MSR-TR-2015-70 | September 2015
글쓴이 Microsoft
-
VC3: Trustworthy Data Analytics in the Cloud using SGX
Felix Schuster, Manuel Costa, Cédric Fournet, Christos Gkantsidis, Marcus Peinado, Gloria Mainar-Ruiz, Mark Russinovich
36th IEEE Symposium on Security and Privacy | May 2015
-
-
-
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
-
Dataset and Lessons Learned from the 2024 SaTML LLM Capture-the-Flag Competition
Edoardo Debenedetti, Javier Rando, Daniel Paleka, Fineas Silaghi, Dragos Albastroiu, Niv Cohen, Yuval Lemberg, Reshmi Ghosh, Ahmed Salem, Rui Wen, Giovanni Cherubin, Santiago Zanella-Béguelin, Robin Schmid, Victor Klemm, Takahiro Miki, Chenhao Li, Stefan Kraft, Mario Fritz, Florian Tramer, Sahar Abdelnabi, Lea Schönherr
NeurIPS 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
편집자: 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, 제 2023 권
-
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
편집자: 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
편집자: Marina Meila and Tong Zhang
-
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
-
Contamination Attacks and Mitigation in Multi-Party Machine Learning
Jamie Hayes, Olya Ohrimenko
Neural Information Processing Systems (NeurIPS) | December 2018
-
-
-
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
-
Dataset and Lessons Learned from the 2024 SaTML LLM Capture-the-Flag Competition
Edoardo Debenedetti, Javier Rando, Daniel Paleka, Fineas Silaghi, Dragos Albastroiu, Niv Cohen, Yuval Lemberg, Reshmi Ghosh, Ahmed Salem, Rui Wen, Giovanni Cherubin, Santiago Zanella-Béguelin, Robin Schmid, Victor Klemm, Takahiro Miki, Chenhao Li, Stefan Kraft, Mario Fritz, Florian Tramer, Sahar Abdelnabi, Lea Schönherr
NeurIPS 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
편집자: 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, 제 2023 권
-
Confidential Computing within an AI Accelerator
Kapil Vaswani, Stavros Volos, Cédric Fournet, Antonio Nino Diaz, Ken Gordon, Balaji Vembu, Sam Webster, David Chisnall, Saurabh Kulkarni, Graham Cunningham , Richard Osborne , Daniel Wilkinson
2023 USENIX Annual Technical Conference | July 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
편집자: 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
편집자: Marina Meila and Tong Zhang
-
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
-
Visor: Privacy-Preserving Video Analytics as a Cloud Service
Rishabh Poddar, Ganesh Ananthanarayanan, Srinath Setty, Stavros Volos, Raluca Ada Popa
29th USENIX Security Symposium | August 2020
CSAW 2020 Applied Research Competition Award (Runner-up)
-
Alleviating Privacy Attacks via Causal Learning
Shruti Tople, Amit Sharma, Aditya V. Nori
International Conference on Machine Learning (ICML) | July 2020
-
An Algorithmic Framework For Differentially Private Data Analysis on Trusted Processors
Joshua Allen, Bolin Ding, Janardhan (Jana) Kulkarni, Harsha Nori, Olga Ohrimenko, Sergey Yekhanin
NeurIPS 2019 | August 2019
-
Contamination Attacks and Mitigation in Multi-Party Machine Learning
Jamie Hayes, Olya Ohrimenko
Neural Information Processing Systems (NeurIPS) | December 2018
-
Graviton: Trusted Execution Environments on GPUs
Stavros Volos, Kapil Vaswani, Rordigo Bruno
13th USENIX Symposium on Operating Systems Design and Implementation | October 2018
-
Oblivious Multi-Party Machine Learning on Trusted Processors
Olya Ohrimenko, Felix Schuster, Cédric Fournet, Aastha Mehta, Sebastian Nowozin, Kapil Vaswani, Manuel Costa
The 25th USENIX Security Symposium 2016 | July 2016
-
Observing and Preventing Leakage in MapReduce
Olya Ohrimenko, Manuel Costa, Cédric Fournet, Christos Gkantsidis, Markulf Kohlweiss, Divya Sharma
MSR-TR-2015-70 | September 2015
글쓴이 Microsoft
-
VC3: Trustworthy Data Analytics in the Cloud using SGX
Felix Schuster, Manuel Costa, Cédric Fournet, Christos Gkantsidis, Marcus Peinado, Gloria Mainar-Ruiz, Mark Russinovich
36th IEEE Symposium on Security and Privacy | May 2015
-
-
-
Confidential Computing within an AI Accelerator
Kapil Vaswani, Stavros Volos, Cédric Fournet, Antonio Nino Diaz, Ken Gordon, Balaji Vembu, Sam Webster, David Chisnall, Saurabh Kulkarni, Graham Cunningham , Richard Osborne , Daniel Wilkinson
2023 USENIX Annual Technical Conference | July 2023
-
Graviton: Trusted Execution Environments on GPUs
Stavros Volos, Kapil Vaswani, Rordigo Bruno
13th USENIX Symposium on Operating Systems Design and Implementation | October 2018
-
-
-
Confidential Computing within an AI Accelerator
Kapil Vaswani, Stavros Volos, Cédric Fournet, Antonio Nino Diaz, Ken Gordon, Balaji Vembu, Sam Webster, David Chisnall, Saurabh Kulkarni, Graham Cunningham , Richard Osborne , Daniel Wilkinson
2023 USENIX Annual Technical Conference | July 2023
-
Visor: Privacy-Preserving Video Analytics as a Cloud Service
Rishabh Poddar, Ganesh Ananthanarayanan, Srinath Setty, Stavros Volos, Raluca Ada Popa
29th USENIX Security Symposium | August 2020
CSAW 2020 Applied Research Competition Award (Runner-up)
-
Graviton: Trusted Execution Environments on GPUs
Stavros Volos, Kapil Vaswani, Rordigo Bruno
13th USENIX Symposium on Operating Systems Design and Implementation | October 2018
-
-
-
Domain Generalization using Causal Matching
Divyat Mahajan, Shruti Tople, Amit Sharma
International Conference on Machine Learning (ICML) | July 2021
-
-
-
Visor: Privacy-Preserving Video Analytics as a Cloud Service
Rishabh Poddar, Ganesh Ananthanarayanan, Srinath Setty, Stavros Volos, Raluca Ada Popa
29th USENIX Security Symposium | August 2020
CSAW 2020 Applied Research Competition Award (Runner-up)
-
-
-
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
-
Dataset and Lessons Learned from the 2024 SaTML LLM Capture-the-Flag Competition
Edoardo Debenedetti, Javier Rando, Daniel Paleka, Fineas Silaghi, Dragos Albastroiu, Niv Cohen, Yuval Lemberg, Reshmi Ghosh, Ahmed Salem, Rui Wen, Giovanni Cherubin, Santiago Zanella-Béguelin, Robin Schmid, Victor Klemm, Takahiro Miki, Chenhao Li, Stefan Kraft, Mario Fritz, Florian Tramer, Sahar Abdelnabi, Lea Schönherr
NeurIPS 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
편집자: Sanjoy Dasgupta, Stephan Mandt, Yingzhen Li
-
Confidential Computing within an AI Accelerator
Kapil Vaswani, Stavros Volos, Cédric Fournet, Antonio Nino Diaz, Ken Gordon, Balaji Vembu, Sam Webster, David Chisnall, Saurabh Kulkarni, Graham Cunningham , Richard Osborne , Daniel Wilkinson
2023 USENIX Annual Technical Conference | July 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
편집자: 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
편집자: Marina Meila and Tong Zhang
-
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
-
Visor: Privacy-Preserving Video Analytics as a Cloud Service
Rishabh Poddar, Ganesh Ananthanarayanan, Srinath Setty, Stavros Volos, Raluca Ada Popa
29th USENIX Security Symposium | August 2020
CSAW 2020 Applied Research Competition Award (Runner-up)
-
Alleviating Privacy Attacks via Causal Learning
Shruti Tople, Amit Sharma, Aditya V. Nori
International Conference on Machine Learning (ICML) | July 2020
-
An Algorithmic Framework For Differentially Private Data Analysis on Trusted Processors
Joshua Allen, Bolin Ding, Janardhan (Jana) Kulkarni, Harsha Nori, Olga Ohrimenko, Sergey Yekhanin
NeurIPS 2019 | August 2019
-
Contamination Attacks and Mitigation in Multi-Party Machine Learning
Jamie Hayes, Olya Ohrimenko
Neural Information Processing Systems (NeurIPS) | December 2018
-
Graviton: Trusted Execution Environments on GPUs
Stavros Volos, Kapil Vaswani, Rordigo Bruno
13th USENIX Symposium on Operating Systems Design and Implementation | October 2018
-
Oblivious Multi-Party Machine Learning on Trusted Processors
Olya Ohrimenko, Felix Schuster, Cédric Fournet, Aastha Mehta, Sebastian Nowozin, Kapil Vaswani, Manuel Costa
The 25th USENIX Security Symposium 2016 | July 2016
-
VC3: Trustworthy Data Analytics in the Cloud using SGX
Felix Schuster, Manuel Costa, Cédric Fournet, Christos Gkantsidis, Marcus Peinado, Gloria Mainar-Ruiz, Mark Russinovich
36th IEEE Symposium on Security and Privacy | May 2015
-
-
-
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, 제 2023 권
-
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
-
-
-
Observing and Preventing Leakage in MapReduce
Olya Ohrimenko, Manuel Costa, Cédric Fournet, Christos Gkantsidis, Markulf Kohlweiss, Divya Sharma
MSR-TR-2015-70 | September 2015
글쓴이 Microsoft
-