Ahmed Salem (CISPA Helmholtz Center for Information Security), Yang Zhang (CISPA Helmholtz Center for Information Security), Mathias Humbert (Swiss Data Science Center, ETH Zurich/EPFL), Pascal Berrang (CISPA Helmholtz Center for Information Security), Mario Fritz (CISPA Helmholtz Center for Information Security), Michael Backes (CISPA Helmholtz Center for Information Security)

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 companies to deploy machine learning as a service (MLaaS). Recently, the first membership inference attack has shown that extraction of information on the training set is possible in such MLaaS settings, which has severe security and privacy implications.

However, the early demonstrations of the feasibility of such attacks have many assumptions on the adversary, such as using multiple so-called shadow models, knowledge of the target model structure, and having a dataset from the same distribution as the target model's training data. We relax all these key assumptions, thereby showing that such attacks are very broadly applicable at low cost and thereby pose a more severe risk than previously thought. We present the most comprehensive study so far on this emerging and developing threat using eight diverse datasets which show the viability of the proposed attacks across domains.

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.

View More Papers

Coconut: Threshold Issuance Selective Disclosure Credentials with Applications to...

Alberto Sonnino (University College London (UCL)), Mustafa Al-Bassam (University College London (UCL)), Shehar Bano (University College London (UCL)), Sarah Meiklejohn (University College London (UCL)), George Danezis (University College London (UCL))

Read More

Privacy Attacks to the 4G and 5G Cellular Paging...

Syed Rafiul Hussain (Purdue University), Mitziu Echeverria (University of Iowa), Omar Chowdhury (University of Iowa), Ninghui Li (Purdue University), Elisa Bertino (Purdue University)

Read More

SANCTUARY: ARMing TrustZone with User-space Enclaves

Ferdinand Brasser (Technische Universität Darmstadt), David Gens (Technische Universität Darmstadt), Patrick Jauernig (Technische Universität Darmstadt), Ahmad-Reza Sadeghi (Technische Universität Darmstadt), Emmanuel Stapf (Technische Universität Darmstadt)

Read More

SABRE: Protecting Bitcoin against Routing Attacks

Maria Apostolaki (ETH Zurich), Gian Marti (ETH Zurich), Jan Müller (ETH Zurich), Laurent Vanbever (ETH Zurich)

Read More