Confidential Deep Learning: Executing Proprietary Models on Untrusted Devices

28 August 2019

Papers citing "Confidential Deep Learning: Executing Proprietary Models on Untrusted Devices"

7 / 7 papers shown

Title
TBNet: A Neural Architectural Defense Framework Facilitating DNN Model Protection in Trusted Execution Environments Ziyu Liu Tong Zhou Yukui Luo Xiaolin Xu 57 2 0 07 May 2024
Fortress: Securing IoT Peripherals with Trusted Execution Environments Peterson Yuhala James Ménétrey Pascal Felber Marcelo Pasin V. Schiavoni 139 1 0 05 Dec 2023
MirrorNet: A TEE-Friendly Framework for Secure On-device DNN Inference Ziyu Liu Yukui Luo Shijin Duan Tong Zhou Xiaolin Xu FedML 55 10 0 16 Nov 2023
Enhancing IoT Security and Privacy with Trusted Execution Environments and Machine Learning Peterson Yuhala 26 0 0 04 May 2023
Machine Learning with Confidential Computing: A Systematization of Knowledge Fan Mo Zahra Tarkhani Hamed Haddadi 94 10 0 22 Aug 2022
Confidential Machine Learning Computation in Untrusted Environments: A Systems Security Perspective Kha Dinh Duy Taehyun Noh Siwon Huh Hojoon Lee 86 9 0 05 Nov 2021
Enclave-Aware Compartmentalization and Secure Sharing with Sirius Zahra Tarkhani Anil Madhavapeddy 16 2 0 03 Sep 2020