16 citations · 40 across the 4 of their papers we have counts for
8 papers
Towards Mass Adoption of Contact Tracing Apps -- Learning from Users' Preferences to Improve App Design
Dana Naous, Manus Bonner, Mathias Humbert +1
Contact tracing apps have become one of the main approaches to control and slow down the spread of COVID-19 and ease up lockdown measures. While these apps can be very effective in…
Image Obfuscation for Privacy-Preserving Machine Learning
Mathilde Raynal, Radhakrishna Achanta, Mathias Humbert
Privacy becomes a crucial issue when outsourcing the training of machine learning (ML) models to cloud-based platforms offering machine-learning services. While solutions based on…
BAAAN: Backdoor Attacks Against Autoencoder and GAN-Based Machine Learning Models
Ahmed Salem, Yannick Sautter, Michael Backes +2
The tremendous progress of autoencoders and generative adversarial networks (GANs) has led to their application to multiple critical tasks, such as fraud detection and sanitized da…
Contact Tracing: An Overview of Technologies and Cyber Risks
Franck Legendre, Mathias Humbert, Alain Mermoud +1
The 2020 COVID-19 pandemic has led to a global lockdown with severe health and economical consequences. As a result, authorities around the globe have expressed their needs for bet…
On (The Lack Of) Location Privacy in Crowdsourcing Applications
Spyros Boukoros, Mathias Humbert, Stefan Katzenbeisser +1
Crowdsourcing enables application developers to benefit from large and diverse datasets at a low cost. Specifically, mobile crowdsourcing (MCS) leverages users' devices as sensors…
ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models
Ahmed Salem, Yang Zhang, Mathias Humbert +3
Machine learning (ML) has become a core component of many real-world applications and training data is a key factor that drives current progress. This huge success has led Internet…