STDLens: Model Hijacking-Resilient Federated Learning for Object
Detection

STDLens: Model Hijacking-Resilient Federated Learning for Object Detection

21 March 2023

Ling Liu

Fatih Ilhan

Papers citing "STDLens: Model Hijacking-Resilient Federated Learning for Object Detection"

8 / 8 papers shown

Title
CRFL: Certifiably Robust Federated Learning against Backdoor Attacks Chulin Xie Minghao Chen Pin-Yu Chen Yue Liu FedML 72 168 0 15 Jun 2021
FLOP: Federated Learning on Medical Datasets using Partial Networks Qiang Yang Jianyi Zhang Weituo Hao Gregory P. Spell Lawrence Carin FedML OOD 50 86 0 10 Feb 2021
FLAME: Taming Backdoors in Federated Learning (Extended Version 1) T. D. Nguyen Phillip Rieger Huili Chen Hossein Yalame Helen Mollering ... Azalia Mirhoseini S. Zeitouni F. Koushanfar A. Sadeghi T. Schneider AAML 56 26 0 06 Jan 2021
Data Poisoning Attacks Against Federated Learning Systems Vale Tolpegin Stacey Truex Mehmet Emre Gursoy Ling Liu FedML 111 653 0 16 Jul 2020
Advances and Open Problems in Federated Learning Peter Kairouz H. B. McMahan Brendan Avent A. Bellet M. Bennis ... Zheng Xu Qiang Yang Felix X. Yu Han Yu Sen Zhao FedML AI4CE 203 6,229 0 10 Dec 2019
Local Model Poisoning Attacks to Byzantine-Robust Federated Learning Minghong Fang Xiaoyu Cao Jinyuan Jia Neil Zhenqiang Gong AAML OOD FedML 101 1,103 0 26 Nov 2019
Can You Really Backdoor Federated Learning? Ziteng Sun Peter Kairouz A. Suresh H. B. McMahan FedML 63 570 0 18 Nov 2019
YOLOv3: An Incremental Improvement Joseph Redmon Ali Farhadi ObjD 105 21,386 0 08 Apr 2018

We use cookies and other tracking technologies to improve your browsing experience on our website, to show you personalized content and targeted ads, to analyze our website traffic, and to understand where our visitors are coming from. See our policy.