activity
20172025
most citedPrivacy Risks of Securing Machine Learning Models against Adversarial Examples

178 citations · 392 across the 10 of their papers we have counts for

collaborators
Showing cs.CRShow all

5 papers · 1 filter

cs.CR2021★ 22 cited

Mitigating Membership Inference Attacks by Self-Distillation Through a Novel Ensemble Architecture

Xinyu Tang, Saeed Mahloujifar, Liwei Song +4

Membership inference attacks are a key measure to evaluate privacy leakage in machine learning (ML) models. These attacks aim to distinguish training members from non-members by ex…

cs.CR2020★ 84 cited

Systematic Evaluation of Privacy Risks of Machine Learning Models

Liwei Song, Prateek Mittal

Machine learning models are prone to memorizing sensitive data, making them vulnerable to membership inference attacks in which an adversary aims to guess if an input sample was us…

cs.CR2020★ 37 cited

Towards Probabilistic Verification of Machine Unlearning

David Marco Sommer, Liwei Song, Sameer Wagh +1

The right to be forgotten, also known as the right to erasure, is the right of individuals to have their data erased from an entity storing it. The status of this long held notion…

cs.CR2017★ 8 cited

Acoustic Denial of Service Attacks on HDDs

Mohammad Shahrad, Arsalan Mosenia, Liwei Song +3

Among storage components, hard disk drives (HDDs) have become the most commonly-used type of non-volatile storage due to their recent technological advances, including, enhanced en…

cs.CR2017★ 37 cited

Inaudible Voice Commands

Liwei Song, Prateek Mittal

Voice assistants like Siri enable us to control IoT devices conveniently with voice commands, however, they also provide new attack opportunities for adversaries. Previous papers a…