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Shruti Tople
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2020 – today
- 2024
- [j4]Ana-Maria Cretu, Daniel Jones, Yves-Alexandre de Montjoye, Shruti Tople:
Investigating the Effect of Misalignment on Membership Privacy in the White-box Setting. Proc. Priv. Enhancing Technol. 2024(3): 407-430 (2024) - [c23]Xiaoyang Wang, Dimitrios Dimitriadis, Sanmi Koyejo, Shruti Tople:
Invariant Aggregator for Defending against Federated Backdoor Attacks. AISTATS 2024: 2728-2736 - [c22]Giovanni Cherubin, Boris Köpf, Andrew Paverd, Shruti Tople, Lukas Wutschitz, Santiago Zanella Béguelin:
Closed-Form Bounds for DP-SGD against Record-level Inference. USENIX Security Symposium 2024 - [i31]Giovanni Cherubin, Boris Köpf, Andrew Paverd, Shruti Tople, Lukas Wutschitz, Santiago Zanella Béguelin:
Closed-Form Bounds for DP-SGD against Record-level Inference. CoRR abs/2402.14397 (2024) - [i30]Shoaib Ahmed Siddiqui, Radhika Gaonkar, Boris Köpf, David Krueger, Andrew Paverd, Ahmed Salem, Shruti Tople, Lukas Wutschitz, Menglin Xia, Santiago Zanella Béguelin:
Permissive Information-Flow Analysis for Large Language Models. CoRR abs/2410.03055 (2024) - 2023
- [j3]Marlon Tobaben, Aliaksandra Shysheya, John Bronskill, Andrew Paverd, Shruti Tople, Santiago Zanella Béguelin, Richard E. Turner, Antti Honkela:
On the Efficacy of Differentially Private Few-shot Image Classification. Trans. Mach. Learn. Res. 2023 (2023) - [c21]Santiago Zanella Béguelin, Lukas Wutschitz, Shruti Tople, Ahmed Salem, Victor Rühle, Andrew Paverd, Mohammad Naseri, Boris Köpf, Daniel Jones:
Bayesian Estimation of Differential Privacy. ICML 2023: 40624-40636 - [c20]Valentin Hartmann, Léo Meynent, Maxime Peyrard, Dimitrios Dimitriadis, Shruti Tople, Robert West:
Distribution Inference Risks: Identifying and Mitigating Sources of Leakage. SaTML 2023: 136-149 - [c19]Ahmed Salem, Giovanni Cherubin, David Evans, Boris Köpf, Andrew Paverd, Anshuman Suri, Shruti Tople, Santiago Zanella Béguelin:
SoK: Let the Privacy Games Begin! A Unified Treatment of Data Inference Privacy in Machine Learning. SP 2023: 327-345 - [c18]Nils Lukas, Ahmed Salem, Robert Sim, Shruti Tople, Lukas Wutschitz, Santiago Zanella Béguelin:
Analyzing Leakage of Personally Identifiable Information in Language Models. SP 2023: 346-363 - [i29]Nils Lukas, Ahmed Salem, Robert Sim, Shruti Tople, Lukas Wutschitz, Santiago Zanella Béguelin:
Analyzing Leakage of Personally Identifiable Information in Language Models. CoRR abs/2302.00539 (2023) - [i28]Marlon Tobaben, Aliaksandra Shysheya, John Bronskill, Andrew Paverd, Shruti Tople, Santiago Zanella Béguelin, Richard E. Turner, Antti Honkela:
On the Efficacy of Differentially Private Few-shot Image Classification. CoRR abs/2302.01190 (2023) - [i27]Ana-Maria Cretu, Daniel Jones, Yves-Alexandre de Montjoye, Shruti Tople:
Re-aligning Shadow Models can Improve White-box Membership Inference Attacks. CoRR abs/2306.05093 (2023) - [i26]Jihye Choi, Shruti Tople, Varun Chandrasekaran, Somesh Jha:
Why Train More? Effective and Efficient Membership Inference via Memorization. CoRR abs/2310.08015 (2023) - [i25]Valentin Hartmann, Anshuman Suri, Vincent Bindschaedler
, David Evans, Shruti Tople, Robert West:
SoK: Memorization in General-Purpose Large Language Models. CoRR abs/2310.18362 (2023) - [i24]Lukas Wutschitz, Boris Köpf, Andrew Paverd, Saravan Rajmohan, Ahmed Salem, Shruti Tople, Santiago Zanella Béguelin, Menglin Xia, Victor Rühle:
Rethinking Privacy in Machine Learning Pipelines from an Information Flow Control Perspective. CoRR abs/2311.15792 (2023) - 2022
- [j2]Yixi Xu, Sumit Mukherjee, Xiyang Liu, Shruti Tople, Rahul Dodhia, Juan M. Lavista Ferres:
Mace: A flexible framework for membership privacy estimation in generative models. Trans. Mach. Learn. Res. 2022 (2022) - [c17]Teodora Baluta
Membership Inference Attacks and Generalization: A Causal Perspective. CCS 2022: 249-262 - [i23]Santiago Zanella Béguelin
Bayesian Estimation of Differential Privacy. CoRR abs/2206.05199 (2022) - [i22]Valentin Hartmann, Léo Meynent, Maxime Peyrard, Dimitrios Dimitriadis, Shruti Tople, Robert West:
Distribution inference risks: Identifying and mitigating sources of leakage. CoRR abs/2209.08541 (2022) - [i21]Teodora Baluta, Shiqi Shen, S. Hitarth, Shruti Tople, Prateek Saxena:
Membership Inference Attacks and Generalization: A Causal Perspective. CoRR abs/2209.08615 (2022) - [i20]Xiaoyang Wang, Dimitrios Dimitriadis, Sanmi Koyejo, Shruti Tople:
Invariant Aggregator for Defending Federated Backdoor Attacks. CoRR abs/2210.01834 (2022) - [i19]Ahmed Salem, Giovanni Cherubin, David Evans, Boris Köpf, Andrew Paverd, Anshuman Suri
SoK: Let The Privacy Games Begin! A Unified Treatment of Data Inference Privacy in Machine Learning. CoRR abs/2212.10986 (2022) - 2021
- [j1]Sameer Wagh, Shruti Tople, Fabrice Benhamouda, Eyal Kushilevitz, Prateek Mittal, Tal Rabin:
Falcon: Honest-Majority Maliciously Secure Framework for Private Deep Learning. Proc. Priv. Enhancing Technol. 2021(1): 188-208 (2021) - [c16]Divyat Mahajan, Shruti Tople, Amit Sharma:
Domain Generalization using Causal Matching. ICML 2021: 7313-7324 - [c15]Santiago Zanella Béguelin, Shruti Tople, Andrew Paverd, Boris Köpf:
Grey-box Extraction of Natural Language Models. ICML 2021: 12278-12286 - [c14]Wanrong Zhang, Shruti Tople, Olga Ohrimenko
Leakage of Dataset Properties in Multi-Party Machine Learning. USENIX Security Symposium 2021: 2687-2704 - [i18]Varun Chandrasekaran, Darren Edge, Somesh Jha, Amit Sharma, Cheng Zhang, Shruti Tople:
Causally Constrained Data Synthesis for Private Data Release. CoRR abs/2105.13144 (2021) - [i17]Divyat Mahajan, Shruti Tople, Amit Sharma:
The Connection between Out-of-Distribution Generalization and Privacy of ML Models. CoRR abs/2110.03369 (2021) - 2020
- [c13]Santiago Zanella Béguelin, Lukas Wutschitz, Shruti Tople, Victor Rühle, Andrew Paverd, Olga Ohrimenko
Analyzing Information Leakage of Updates to Natural Language Models. CCS 2020: 363-375 - [c12]Yaoqi Jia, Shruti Tople, Tarik Moataz, Deli Gong, Prateek Saxena, Zhenkai Liang:
Robust P2P Primitives Using SGX Enclaves. ICDCS 2020: 1185-1186 - [c11]Shruti Tople, Amit Sharma, Aditya Nori:
Alleviating Privacy Attacks via Causal Learning. ICML 2020: 9537-9547 - [c10]Yaoqi Jia, Shruti Tople, Tarik Moataz, Deli Gong, Prateek Saxena, Zhenkai Liang:
Robust P2P Primitives Using SGX Enclaves. RAID 2020: 209-224 - [i16]Bijeeta Pal, Shruti Tople:
To Transfer or Not to Transfer: Misclassification Attacks Against Transfer Learned Text Classifiers. CoRR abs/2001.02438 (2020) - [i15]Sameer Wagh, Shruti Tople, Fabrice Benhamouda, Eyal Kushilevitz, Prateek Mittal, Tal Rabin:
FALCON: Honest-Majority Maliciously Secure Framework for Private Deep Learning. CoRR abs/2004.02229 (2020) - [i14]Wanrong Zhang, Shruti Tople, Olga Ohrimenko:
Dataset-Level Attribute Leakage in Collaborative Learning. CoRR abs/2006.07267 (2020) - [i13]Divyat Mahajan, Shruti Tople, Amit Sharma:
Domain Generalization using Causal Matching. CoRR abs/2006.07500 (2020) - [i12]Dongge Han, Shruti Tople, Alex Rogers, Michael J. Wooldridge, Olga Ohrimenko, Sebastian Tschiatschek:
Replication-Robust Payoff-Allocation with Applications in Machine Learning Marketplaces. CoRR abs/2006.14583 (2020) - [i11]Anshul Aggarwal, Trevor E. Carlson, Reza Shokri, Shruti Tople:
SOTERIA: In Search of Efficient Neural Networks for Private Inference. CoRR abs/2007.12934 (2020)
2010 – 2019
- 2019
- [c9]Shruti Tople, Yaoqi Jia, Prateek Saxena:
PRO-ORAM: Practical Read-Only Oblivious RAM. RAID 2019: 197-211 - [i10]Shruti Tople, Amit Sharma, Aditya Nori:
Alleviating Privacy Attacks via Causal Learning. CoRR abs/1909.12732 (2019) - [i9]Olga Ohrimenko, Shruti Tople, Sebastian Tschiatschek:
Collaborative Machine Learning Markets with Data-Replication-Robust Payments. CoRR abs/1911.09052 (2019) - [i8]Stephanie L. Hyland, Shruti Tople:
On the Intrinsic Privacy of Stochastic Gradient Descent. CoRR abs/1912.02919 (2019) - [i7]Shruti Tople, Marc Brockschmidt, Boris Köpf, Olga Ohrimenko, Santiago Zanella Béguelin
Analyzing Privacy Loss in Updates of Natural Language Models. CoRR abs/1912.07942 (2019) - 2018
- [c8]Shruti Tople, Soyeon Park, Min Suk Kang, Prateek Saxena:
VeriCount: Verifiable Resource Accounting Using Hardware and Software Isolation. ACNS 2018: 657-677 - [i6]Shruti Tople, Karan Grover, Shweta Shinde
Privado: Practical and Secure DNN Inference. CoRR abs/1810.00602 (2018) - [i5]Shruti Tople, Yaoqi Jia, Prateek Saxena:
PRO-ORAM: Constant Latency Read-Only Oblivious RAM. IACR Cryptol. ePrint Arch. 2018: 220 (2018) - 2017
- [c7]Shruti Tople, Prateek Saxena:
On the Trade-Offs in Oblivious Execution Techniques. DIMVA 2017: 25-47 - [c6]Amrit Kumar, Clément Fischer, Shruti Tople, Prateek Saxena:
A Traceability Analysis of Monero's Blockchain. ESORICS (2) 2017: 153-173 - [c5]Shweta Shinde, Dat Le Tien, Shruti Tople, Prateek Saxena:
Panoply: Low-TCB Linux Applications With SGX Enclaves. NDSS 2017 - [i4]Yaoqi Jia, Shruti Tople, Tarik Moataz, Deli Gong, Prateek Saxena, Zhenkai Liang:
Robust Synchronous P2P Primitives Using SGX Enclaves. IACR Cryptol. ePrint Arch. 2017: 180 (2017) - [i3]Amrit Kumar, Clément Fischer, Shruti Tople, Prateek Saxena:
A Traceability Analysis of Monero's Blockchain. IACR Cryptol. ePrint Arch. 2017: 338 (2017) - [i2]Shruti Tople, Hung Dang, Prateek Saxena, Ee-Chien Chang:
PermuteRam: Optimizing Oblivious Computation for Efficiency. IACR Cryptol. ePrint Arch. 2017: 885 (2017) - 2016
- [c4]Shiqi Shen, Shruti Tople, Prateek Saxena:
Auror: defending against poisoning attacks in collaborative deep learning systems. ACSAC 2016: 508-519 - [c3]Yaoqi Jia, Tarik Moataz, Shruti Tople, Prateek Saxena:
OblivP2P: An Oblivious Peer-to-Peer Content Sharing System. USENIX Security Symposium 2016: 945-962 - 2014
- [i1]Hoon Wei Lim, Shruti Tople, Prateek Saxena, Ee-Chien Chang:
Faster Secure Arithmetic Computation Using Switchable Homomorphic Encryption. IACR Cryptol. ePrint Arch. 2014: 539 (2014) - 2013
- [c2]Shruti Tople, Shweta Shinde
AUTOCRYPT: enabling homomorphic computation on servers to protect sensitive web content. CCS 2013: 1297-1310 - [c1]Xinshu Dong, Zhaofeng Chen, Hossein Siadati
Protecting sensitive web content from client-side vulnerabilities with CRYPTONS. CCS 2013: 1311-1324
Coauthor Index
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last updated on 2024-11-08 20:32 CET by the dblp team
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