When Federated Learning meets Watermarking: A Comprehensive Overview of Techniques for Intellectual Property Protection

7 August 2023

Papers citing "When Federated Learning meets Watermarking: A Comprehensive Overview of Techniques for Intellectual Property Protection"

32 / 32 papers shown

Title
Federated Learning of Gboard Language Models with Differential Privacy Zheng Xu Yanxiang Zhang Galen Andrew Christopher A. Choquette-Choo Peter Kairouz H. B. McMahan Jesse Rosenstock Yuanbo Zhang FedML 88 81 0 29 May 2023
FedZKP: Federated Model Ownership Verification with Zero-knowledge Proof Wenyuan Yang Yuguo Yin Gongxi Zhu Hanlin Gu Lixin Fan Xiaochun Cao Qiang Yang FedML 58 9 0 08 May 2023
Mixer: DNN Watermarking using Image Mixup Kassem Kallas Teddy Furon WIGM 64 4 0 06 Dec 2022
Watermarking in Secure Federated Learning: A Verification Framework Based on Client-Side Backdooring Wenyuan Yang Shuo Shao Yue Yang Xiyao Liu Ximeng Liu Zhihua Xia Gerald Schaefer Hui Fang FedML 47 23 0 14 Nov 2022
DICTION:DynamIC robusT whIte bOx watermarkiNg scheme for deep neural networks Reda Bellafqira Gouenou Coatrieux 81 6 0 27 Oct 2022
Towards Practical Watermark for Deep Neural Networks in Federated Learning Fangqi Li Shi-Lin Wang Alan Wee-Chung Liew FedML 42 11 0 07 May 2021
TenSEAL: A Library for Encrypted Tensor Operations Using Homomorphic Encryption Ayoub Benaissa Bilal Retiat Bogdan Cebere Alaa Eddine Belfedhal FedML 89 138 0 07 Apr 2021
A survey of deep neural network watermarking techniques Yue Li Hongxia Wang Mauro Barni 110 146 0 16 Mar 2021
Spread-Transform Dither Modulation Watermarking of Deep Neural Network Yue Li B. Tondi Mauro Barni 34 48 0 28 Dec 2020
Passport-aware Normalization for Deep Model Protection Jie Zhang Dongdong Chen Jing Liao Weiming Zhang G. Hua Nenghai Yu AAML 60 71 0 29 Oct 2020
A Systematic Review on Model Watermarking for Neural Networks Franziska Boenisch AAML 66 69 0 25 Sep 2020
Flower: A Friendly Federated Learning Research Framework Daniel J. Beutel Taner Topal Akhil Mathur Xinchi Qiu Javier Fernandez-Marques ... Lorenzo Sani Kwing Hei Li Titouan Parcollet Pedro Porto Buarque de Gusmão Nicholas D. Lane FedML 140 815 0 28 Jul 2020
IBM Federated Learning: an Enterprise Framework White Paper V0.1 Heiko Ludwig Nathalie Baracaldo Gegi Thomas Yi Zhou Ali Anwar ... Sean Laguna Mikhail Yurochkin Mayank Agarwal Ebube Chuba Annie Abay FedML 194 163 0 22 Jul 2020
Data Poisoning Attacks Against Federated Learning Systems Vale Tolpegin Stacey Truex Mehmet Emre Gursoy Ling Liu FedML 118 660 0 16 Jul 2020
Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization Jianyu Wang Qinghua Liu Hao Liang Gauri Joshi H. Vincent Poor MoMe FedML 70 1,348 0 15 Jul 2020
Two-Phase Multi-Party Computation Enabled Privacy-Preserving Federated Learning Renuga Kanagavelu Zengxiang Li J. Samsudin Yechao Yang Feng Yang Rick Siow Mong Goh Mervyn Cheah Praewpiraya Wiwatphonthana K. Akkarajitsakul Shangguang Wang FedML 152 89 0 25 May 2020
DarkneTZ: Towards Model Privacy at the Edge using Trusted Execution Environments Fan Mo Ali Shahin Shamsabadi Kleomenis Katevas Soteris Demetriou Ilias Leontiadis Andrea Cavallaro Hamed Haddadi FedML 64 181 0 12 Apr 2020
Learning to Detect Malicious Clients for Robust Federated Learning Suyi Li Yong Cheng Wei Wang Yang Liu Tianjian Chen AAML FedML 109 225 0 01 Feb 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 268 6,285 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 105 1,121 0 26 Nov 2019
BrainTorrent: A Peer-to-Peer Environment for Decentralized Federated Learning Abhijit Guha Roy Shayan Siddiqui Sebastian Polsterl Nassir Navab Christian Wachinger FedML OOD MedIm 65 309 0 16 May 2019
Object Detection in 20 Years: A Survey Zhengxia Zou Keyan Chen Zhenwei Shi Yuhong Guo Jieping Ye VLM ObjD AI4TS 123 2,378 0 13 May 2019
How to Prove Your Model Belongs to You: A Blind-Watermark based Framework to Protect Intellectual Property of DNN Zheng Li Chengyu Hu Yang Zhang Shanqing Guo AAML 55 173 0 05 Mar 2019
Split learning for health: Distributed deep learning without sharing raw patient data Praneeth Vepakomma O. Gupta Tristan Swedish Ramesh Raskar FedML 118 710 0 03 Dec 2018
Exploiting Unintended Feature Leakage in Collaborative Learning Luca Melis Congzheng Song Emiliano De Cristofaro Vitaly Shmatikov FedML 157 1,481 0 10 May 2018
Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates Dong Yin Yudong Chen Kannan Ramchandran Peter L. Bartlett OOD FedML 124 1,516 0 05 Mar 2018
Turning Your Weakness Into a Strength: Watermarking Deep Neural Networks by Backdooring Yossi Adi Carsten Baum Moustapha Cissé Benny Pinkas Joseph Keshet 65 682 0 13 Feb 2018
Machine Learning Models that Remember Too Much Congzheng Song Thomas Ristenpart Vitaly Shmatikov VLM 73 518 0 22 Sep 2017
Embedding Watermarks into Deep Neural Networks Yusuke Uchida Yuki Nagai S. Sakazawa Shiníchi Satoh 122 610 0 15 Jan 2017
Deep Learning with Differential Privacy Martín Abadi Andy Chu Ian Goodfellow H. B. McMahan Ilya Mironov Kunal Talwar Li Zhang FedML SyDa 216 6,162 0 01 Jul 2016
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 408 17,593 0 17 Feb 2016
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 282 19,121 0 20 Dec 2014