USENIX

Enabling AI Network Cross-Layer Design and Operations with Arcadia: A Simulation Platform at Scale

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

Here, There and Everywhere: The Past, the Present and the Future of Local Storage in Cloud

Cloud local storage has been a popular service among many vendors thanks to its near-physical performance and affordable price. In this paper, we revisit the evolution of the cloud local storage at ...
USENIX

From Risk to Resilience: Towards Assessing and Mitigating the Risk of Data Reconstruction Attacks in Federated Learning

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

BLuEMan: A Stateful Simulation-based Fuzzing Framework for Open-Source RTOS Bluetooth Low Energy Protocol Stacks

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

No Way to Sign Out? Unpacking Non-Compliance with Google Play's App Account Deletion Requirements

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

Your Shield is My Sword: A Persistent Denial-of-Service Attack via the Reuse of Unvalidated Caches in DNSSEC Validation

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

"We are not Future-ready": Understanding AI Privacy Risks and Existing Mitigation Strategies from the Perspective of AI Developers in Europe

The proliferation of AI has sparked privacy concerns related to training data, model interfaces, downstream applications, and more. We interviewed 25 AI developers based in Europe to understand which ...
USENIX

WLB-LLM: Workload-Balanced 4D Parallelism for Large Language Model Training

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

Generated Data with Fake Privacy: Hidden Dangers of Fine-tuning Large Language Models on Generated Data

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

Whispering Under the Eaves: Protecting User Privacy Against Commercial and LLM-powered Automatic Speech Recognition Systems

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

ChainPatrol: Balancing Attack Detection and Classification with Performance Overhead for Service Function Chains Using Virtual Trailers

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

Metis: Fast Automatic Distributed Training on Heterogeneous GPUs

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 ...