Enhanced Membership Inference Attacks against Machine Learning Models

Author:

Ye Jiayuan1,Maddi Aadyaa1,Murakonda Sasi Kumar2,Bindschaedler Vincent3,Shokri Reza1

Affiliation:

1. National University of Singapore (NUS), Singapore, Singapore

2. Privitar Labs, London, United Kingdom

3. University of Florida, Gainesville, FL, USA

Funder

the National Research Foundation, Singapore under its Strategic Capability Research Centres Funding Initiative

Google PDPO faculty research award

Intel within the www.private-ai.org center

the NUS Early Career Research Award

Meta faculty research award

Publisher

ACM

Reference37 articles.

1. Membership Privacy in MicroRNA-based Studies

2. Membership Inference Attacks From First Principles

3. Nicholas Carlini , Chang Liu , Úlfar Erlingsson , Jernej Kos , and Dawn Song . 2019. The secret sharer: Evaluating and testing unintended memorization in neural networks . In 28th $$USENIX$$ Security Symposium ($$USENIX$$ Security 19). 267--284. Nicholas Carlini, Chang Liu, Úlfar Erlingsson, Jernej Kos, and Dawn Song. 2019. The secret sharer: Evaluating and testing unintended memorization in neural networks. In 28th $$USENIX$$ Security Symposium ($$USENIX$$ Security 19). 267--284.

4. On the Privacy Risks of Algorithmic Fairness

5. Christopher A Choquette-Choo , Florian Tramer , Nicholas Carlini , and Nicolas Papernot . 2021 . Label-only membership inference attacks . In International Conference on Machine Learning. 1964--1974 . Christopher A Choquette-Choo, Florian Tramer, Nicholas Carlini, and Nicolas Papernot. 2021. Label-only membership inference attacks. In International Conference on Machine Learning. 1964--1974.

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