Artifacts for Publication - Fingerprints in the Wild: An Adversarial Study of Behavior Beyond Standard Attack Models and Implications for Robustness Evaluation
Abstract
This repository contains the study materials, anonymized data, and analysis code for the study "Fingerprints in the Wild: An Adversarial Study of Behavior Beyond Standard Attack Models and Implications for Robustness Evaluation" submitted to USENIX Security 2026. We provide these assets to ensure the transparency, replicability, and verifiability of our findings.
Fields of Study & Subjects
Adversarial Robustness in Machine Learning
Security and Verification in Computing
Network Security and Intrusion Detection
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 6 February 2026