A Reputation Mechanism Is All You Need: Collaborative Fairness and Adversarial Robustness in Federated Learning

20 November 2020

Papers citing "A Reputation Mechanism Is All You Need: Collaborative Fairness and Adversarial Robustness in Federated Learning"

40 / 40 papers shown

Title
Trial and Trust: Addressing Byzantine Attacks with Comprehensive Defense Strategy Gleb Molodtsov Daniil Medyakov Sergey Skorik Nikolas Khachaturov Shahane Tigranyan Vladimir Aletov A. Avetisyan Martin Takáč Aleksandr Beznosikov AAML 35 0 0 12 May 2025
FedPCA: Noise-Robust Fair Federated Learning via Performance-Capacity Analysis Nannan Wu Zengqiang Yan Nong Sang Li Yu Chang Wen Chen 43 0 0 13 Mar 2025
MAB-Based Channel Scheduling for Asynchronous Federated Learning in Non-Stationary Environments Zehan Li Yubo Yang Tao Yang X. Wu Ziyu Guo Bo Hu 64 0 0 03 Mar 2025
Dual Defense: Enhancing Privacy and Mitigating Poisoning Attacks in Federated Learning Runhua Xu Shiqi Gao Chao Li J. Joshi Jianxin Li 43 2 0 08 Feb 2025
CYCle: Choosing Your Collaborators Wisely to Enhance Collaborative Fairness in Decentralized Learning Nurbek Tastan Samuel Horváth Karthik Nandakumar FedML 69 0 0 21 Jan 2025
TPFL: A Trustworthy Personalized Federated Learning Framework via Subjective Logic Jinqian Chen Jihua Zhu 31 0 0 16 Oct 2024
FRIDA: Free-Rider Detection using Privacy Attacks Pol G. Recasens Ádám Horváth Alberto Gutierrez-Torre Jordi Torres Josep Ll. Berral Balázs Pejó FedML 26 0 0 07 Oct 2024
On ADMM in Heterogeneous Federated Learning: Personalization, Robustness, and Fairness Shengkun Zhu Jinshan Zeng Sheng Wang Yuan Sun Xiaodong Li Yuan Yao Zhiyong Peng 46 0 0 23 Jul 2024
Privacy-preserving gradient-based fair federated learning Janis Adamek M. S. Darup FedML 19 0 0 18 Jul 2024
Linkage on Security, Privacy and Fairness in Federated Learning: New Balances and New Perspectives Linlin Wang Tianqing Zhu Wanlei Zhou Philip S. Yu 34 1 0 16 Jun 2024
Data Quality in Edge Machine Learning: A State-of-the-Art Survey M. D. Belgoumri Mohamed Reda Bouadjenek Sunil Aryal Hakim Hacid 41 1 0 01 Jun 2024
ACE: A Model Poisoning Attack on Contribution Evaluation Methods in Federated Learning Zhangchen Xu Fengqing Jiang Luyao Niu Jinyuan Jia Bo Li Radha Poovendran FedML 52 1 0 31 May 2024
FedSAC: Dynamic Submodel Allocation for Collaborative Fairness in Federated Learning Zihui Wang Zheng Wang Lingjuan Lyu Zhaopeng Peng Zhicheng Yang Chenglu Wen Rongshan Yu Cheng-i Wang Xiaoliang Fan FedML 35 2 0 28 May 2024
FACT or Fiction: Can Truthful Mechanisms Eliminate Federated Free Riding? Marco Bornstein Amrit Singh Bedi Abdirisak Mohamed Furong Huang FedML 41 0 0 22 May 2024
Towards Fair Graph Federated Learning via Incentive Mechanisms Chenglu Pan Jiarong Xu Yue Yu Ziqi Yang Qingbiao Wu Chunping Wang Lei Chen Yang Yang FedML 17 8 0 20 Dec 2023
On the Effect of Defections in Federated Learning and How to Prevent Them Minbiao Han Kumar Kshitij Patel Han Shao Lingxiao Wang FedML 38 3 0 28 Nov 2023
Towards Realistic Mechanisms That Incentivize Federated Participation and Contribution Marco Bornstein Amrit Singh Bedi Anit Kumar Sahu Furqan Khan Furong Huang FedML 11 0 0 20 Oct 2023
Hire When You Need to: Gradual Participant Recruitment for Auction-based Federated Learning Xavier Tan Han Yu FedML 37 3 0 04 Oct 2023
martFL: Enabling Utility-Driven Data Marketplace with a Robust and Verifiable Federated Learning Architecture Qi Li Zhuotao Liu Qi Li Ke Xu 14 12 0 03 Sep 2023
Fairness and Privacy in Federated Learning and Their Implications in Healthcare Navya Annapareddy Jade F. Preston Judy Fox FedML 16 3 0 15 Aug 2023
Towards Fair and Privacy Preserving Federated Learning for the Healthcare Domain Navya Annapareddy Yingzheng Liu Judy Fox OOD 17 2 0 03 Aug 2023
Fairness and Privacy-Preserving in Federated Learning: A Survey Taki Hasan Rafi Faiza Anan Noor Tahmid Hussain Dong-Kyu Chae FedML 35 39 0 14 Jun 2023
Trustworthy Federated Learning: A Survey A. Tariq M. Serhani F. Sallabi Tariq Qayyum E. Barka K. Shuaib FedML 30 9 0 19 May 2023
Patchwork Learning: A Paradigm Towards Integrative Analysis across Diverse Biomedical Data Sources Suraj Rajendran Weishen Pan M. Sabuncu Yong Chen Jiayu Zhou Fei Wang 54 14 0 10 May 2023
Secure Federated Learning against Model Poisoning Attacks via Client Filtering D. Yaldiz Tuo Zhang Salman Avestimehr AAML FedML 18 13 0 31 Mar 2023
FedGS: Federated Graph-based Sampling with Arbitrary Client Availability Zhilin Wang Xiaoliang Fan Jianzhong Qi Haibing Jin Peizhen Yang Siqi Shen Cheng-i Wang FedML 30 13 0 25 Nov 2022
Robust Distributed Learning Against Both Distributional Shifts and Byzantine Attacks Guanqiang Zhou Ping Xu Yue Wang Zhi Tian OOD FedML 30 4 0 29 Oct 2022
PASS: A Parameter Audit-based Secure and Fair Federated Learning Scheme against Free-Rider Attack Jianhua Wang Xiaolin Chang J. Misic Vojislav B. Mišić Yixiang Wang 16 7 0 15 Jul 2022
Federated and Transfer Learning: A Survey on Adversaries and Defense Mechanisms Ehsan Hallaji R. Razavi-Far M. Saif AAML FedML 21 13 0 05 Jul 2022
Rethinking the Defense Against Free-rider Attack From the Perspective of Model Weight Evolving Frequency Jinyin Chen Mingjun Li Tao Liu Haibin Zheng Yao Cheng Changting Lin AAML 21 10 0 11 Jun 2022
FedCorr: Multi-Stage Federated Learning for Label Noise Correction Jingyi Xu Zihan Chen Tony Q. S. Quek Kai Fong Ernest Chong FedML 16 85 0 10 Apr 2022
Towards Verifiable Federated Learning Yanci Zhang Hanyou Yu FedML 14 21 0 15 Feb 2022
A Fair and Efficient Hybrid Federated Learning Framework based on XGBoost for Distributed Power Prediction Haizhou Liu Xuan Zhang Xinwei Shen Hongbin Sun FedML 24 6 0 08 Jan 2022
Auction-Based Ex-Post-Payment Incentive Mechanism Design for Horizontal Federated Learning with Reputation and Contribution Measurement Jingwen Zhang Yuezhou Wu Rong Pan FedML 16 19 0 07 Jan 2022
Towards Fairness-Aware Federated Learning Yuxin Shi Han Yu Cyril Leung FedML 21 79 0 02 Nov 2021
FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping Xiaoyu Cao Minghong Fang Jia Liu Neil Zhenqiang Gong FedML 117 611 0 27 Dec 2020
Privacy and Robustness in Federated Learning: Attacks and Defenses Lingjuan Lyu Han Yu Xingjun Ma Chen Chen Lichao Sun Jun Zhao Qiang Yang Philip S. Yu FedML 183 355 0 07 Dec 2020
Collaborative Machine Learning with Incentive-Aware Model Rewards Rachael Hwee Ling Sim Yehong Zhang M. Chan Hsiang Low FedML 117 123 0 24 Oct 2020
Threats to Federated Learning: A Survey Lingjuan Lyu Han Yu Qiang Yang FedML 202 434 0 04 Mar 2020
Convolutional Neural Networks for Sentence Classification Yoon Kim AILaw VLM 255 13,364 0 25 Aug 2014