Search Results for author: Mathias Humbert

Found 6 papers, 4 papers with code

Graph Unlearning

1 code implementation27 Mar 2021 Min Chen, Zhikun Zhang, Tianhao Wang, Michael Backes, Mathias Humbert, Yang Zhang

In the context of machine learning (ML), it requires the ML model provider to remove the data subject's data from the training set used to build the ML model, a process known as \textit{machine unlearning}.

When Machine Unlearning Jeopardizes Privacy

1 code implementation5 May 2020 Min Chen, Zhikun Zhang, Tianhao Wang, Michael Backes, Mathias Humbert, Yang Zhang

More importantly, we show that our attack in multiple cases outperforms the classical membership inference attack on the original ML model, which indicates that machine unlearning can have counterproductive effects on privacy.

Inference Attack Membership Inference Attack

On (The Lack Of) Location Privacy in Crowdsourcing Applications

1 code implementation15 Jan 2019 Spyros Boukoros, Mathias Humbert, Stefan Katzenbeisser, Carmela Troncoso

Crowdsourcing enables application developers to benefit from large and diverse datasets at a low cost.

Cryptography and Security

ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models

6 code implementations4 Jun 2018 Ahmed Salem, Yang Zhang, Mathias Humbert, Pascal Berrang, Mario Fritz, Michael Backes

In addition, we propose the first effective defense mechanisms against such broader class of membership inference attacks that maintain a high level of utility of the ML model.

BIG-bench Machine Learning Inference Attack +1

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