Shruti Tople

According to our database1, Shruti Tople authored at least 46 papers between 2013 and 2024.

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Bibliography

2024
Investigating the Effect of Misalignment on Membership Privacy in the White-box Setting.
Proc. Priv. Enhancing Technol., 2024

Permissive Information-Flow Analysis for Large Language Models.
CoRR, 2024

Closed-Form Bounds for DP-SGD against Record-level Inference.
Proceedings of the 33rd USENIX Security Symposium, 2024

Invariant Aggregator for Defending against Federated Backdoor Attacks.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023
On the Efficacy of Differentially Private Few-shot Image Classification.
Trans. Mach. Learn. Res., 2023

Rethinking Privacy in Machine Learning Pipelines from an Information Flow Control Perspective.
CoRR, 2023

SoK: Memorization in General-Purpose Large Language Models.
CoRR, 2023

Why Train More? Effective and Efficient Membership Inference via Memorization.
CoRR, 2023

Re-aligning Shadow Models can Improve White-box Membership Inference Attacks.
CoRR, 2023

SoK: Let the Privacy Games Begin! A Unified Treatment of Data Inference Privacy in Machine Learning.
Proceedings of the 44th IEEE Symposium on Security and Privacy, 2023

Analyzing Leakage of Personally Identifiable Information in Language Models.
Proceedings of the 44th IEEE Symposium on Security and Privacy, 2023

Distribution Inference Risks: Identifying and Mitigating Sources of Leakage.
Proceedings of the 2023 IEEE Conference on Secure and Trustworthy Machine Learning, 2023

Bayesian Estimation of Differential Privacy.
Proceedings of the International Conference on Machine Learning, 2023

2022
Mace: A flexible framework for membership privacy estimation in generative models.
Trans. Mach. Learn. Res., 2022

Invariant Aggregator for Defending Federated Backdoor Attacks.
CoRR, 2022

Membership Inference Attacks and Generalization: A Causal Perspective.
Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security, 2022

2021
Falcon: Honest-Majority Maliciously Secure Framework for Private Deep Learning.
Proc. Priv. Enhancing Technol., 2021

The Connection between Out-of-Distribution Generalization and Privacy of ML Models.
CoRR, 2021

Causally Constrained Data Synthesis for Private Data Release.
CoRR, 2021

Leakage of Dataset Properties in Multi-Party Machine Learning.
Proceedings of the 30th USENIX Security Symposium, 2021

Domain Generalization using Causal Matching.
Proceedings of the 38th International Conference on Machine Learning, 2021

Grey-box Extraction of Natural Language Models.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
SOTERIA: In Search of Efficient Neural Networks for Private Inference.
CoRR, 2020

Replication-Robust Payoff-Allocation with Applications in Machine Learning Marketplaces.
CoRR, 2020

Dataset-Level Attribute Leakage in Collaborative Learning.
CoRR, 2020

To Transfer or Not to Transfer: Misclassification Attacks Against Transfer Learned Text Classifiers.
CoRR, 2020

Alleviating Privacy Attacks via Causal Learning.
Proceedings of the 37th International Conference on Machine Learning, 2020

Robust P2P Primitives Using SGX Enclaves.
Proceedings of the 40th IEEE International Conference on Distributed Computing Systems, 2020

Analyzing Information Leakage of Updates to Natural Language Models.
Proceedings of the CCS '20: 2020 ACM SIGSAC Conference on Computer and Communications Security, 2020

2019
Analyzing Privacy Loss in Updates of Natural Language Models.
CoRR, 2019

On the Intrinsic Privacy of Stochastic Gradient Descent.
CoRR, 2019

Collaborative Machine Learning Markets with Data-Replication-Robust Payments.
CoRR, 2019

PRO-ORAM: Practical Read-Only Oblivious RAM.
Proceedings of the 22nd International Symposium on Research in Attacks, 2019

2018
PRO-ORAM: Constant Latency Read-Only Oblivious RAM.
IACR Cryptol. ePrint Arch., 2018

Privado: Practical and Secure DNN Inference.
CoRR, 2018

VeriCount: Verifiable Resource Accounting Using Hardware and Software Isolation.
Proceedings of the Applied Cryptography and Network Security, 2018

2017
PermuteRam: Optimizing Oblivious Computation for Efficiency.
IACR Cryptol. ePrint Arch., 2017

A Traceability Analysis of Monero's Blockchain.
IACR Cryptol. ePrint Arch., 2017

Robust Synchronous P2P Primitives Using SGX Enclaves.
IACR Cryptol. ePrint Arch., 2017

Panoply: Low-TCB Linux Applications With SGX Enclaves.
Proceedings of the 24th Annual Network and Distributed System Security Symposium, 2017

On the Trade-Offs in Oblivious Execution Techniques.
Proceedings of the Detection of Intrusions and Malware, and Vulnerability Assessment, 2017

2016
OblivP2P: An Oblivious Peer-to-Peer Content Sharing System.
Proceedings of the 25th USENIX Security Symposium, 2016

Auror: defending against poisoning attacks in collaborative deep learning systems.
Proceedings of the 32nd Annual Conference on Computer Security Applications, 2016

2014
Faster Secure Arithmetic Computation Using Switchable Homomorphic Encryption.
IACR Cryptol. ePrint Arch., 2014

2013
AUTOCRYPT: enabling homomorphic computation on servers to protect sensitive web content.
Proceedings of the 2013 ACM SIGSAC Conference on Computer and Communications Security, 2013

Protecting sensitive web content from client-side vulnerabilities with CRYPTONS.
Proceedings of the 2013 ACM SIGSAC Conference on Computer and Communications Security, 2013


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