USENIX

A NEW HOPE: Contextual Privacy Policies for Mobile Applications and An Approach Toward Automated Generation

USENIX is committed to Open Access to the research presented at our events. Papers and proceedings are freely available to everyone once the event begins. Any video, audio, and/or slides that are ...
USENIX

USENIX Security '25 Schedule

9:00 am–10:30 am USENIX Security '25 Technical Sessions Ballrooms 6A–6C, Room 611–614, Room 606–609 10:30 am–11:00 am Coffee and Tea Break Room 605–610 11:00 am–12:30 pm USENIX Security '25 Technical ...
USENIX

Synthetic Data – Anonymisation Groundhog Day

Synthetic data has been advertised as a silver-bullet solution to privacy-preserving data publishing that addresses the shortcomings of traditional anonymisation techniques. The promise is that ...
USENIX

Monoxide: Scale out Blockchains with Asynchronous Consensus Zones

USENIX is committed to Open Access to the research presented at our events. Papers and proceedings are freely available to everyone once the event begins. Any video, audio, and/or slides that are ...
USENIX

Rosetta: Enabling Robust TLS Encrypted Traffic Classification in Diverse Network Environments with TCP-Aware Traffic Augmentation

USENIX is committed to Open Access to the research presented at our events. Papers and proceedings are freely available to everyone once the event begins. Any video, audio, and/or slides that are ...
USENIX

AutoFHE: Automated Adaption of CNNs for Efficient Evaluation over FHE

USENIX is committed to Open Access to the research presented at our events. Papers and proceedings are freely available to everyone once the event begins. Any video, audio, and/or slides that are ...
USENIX

Android SmartTVs Vulnerability Discovery via Log-Guided Fuzzing

USENIX is committed to Open Access to the research presented at our events. Papers and proceedings are freely available to everyone once the event begins. Any video, audio, and/or slides that are ...
USENIX

You Can't See Me: Physical Removal Attacks on LiDAR-based Autonomous Vehicles Driving Frameworks

USENIX is committed to Open Access to the research presented at our events. Papers and proceedings are freely available to everyone once the event begins. Any video, audio, and/or slides that are ...
USENIX

INFaaS: Automated Model-less Inference Serving

USENIX is committed to Open Access to the research presented at our events. Papers and proceedings are freely available to everyone once the event begins. Any video, audio, and/or slides that are ...
USENIX

GAZELLE: A Low Latency Framework for Secure Neural Network Inference

USENIX is committed to Open Access to the research presented at our events. Papers and proceedings are freely available to everyone once the event begins. Any video, audio, and/or slides that are ...
USENIX

zpoline: a system call hook mechanism based on binary rewriting

This paper presents zpoline, a system call hook mechanism for x86-64 CPUs. zpoline employs binary rewriting and offers seven advantages: 1) low hook overhead, 2) exhaustive hooking, 3) it does not ...
USENIX

Identifying Harmful Media in End-to-End Encrypted Communication: Efficient Private Membership Computation

USENIX is committed to Open Access to the research presented at our events. Papers and proceedings are freely available to everyone once the event begins. Any video, audio, and/or slides that are ...