Poisoning Deep Learning Based Recommender Model in Federated Learning Scenarios

26 April 2022

Papers citing "Poisoning Deep Learning Based Recommender Model in Federated Learning Scenarios"

7 / 7 papers shown

Title
Preventing the Popular Item Embedding Based Attack in Federated Recommendations J. Zhang Huan Li Dazhong Rong Yan Zhao Ke Chen Lidan Shou AAML 64 4 0 18 Feb 2025
Poisoning Decentralized Collaborative Recommender System and Its Countermeasures Ruiqi Zheng Liang Qu Tong Chen Kai Zheng Yuhui Shi Hongzhi Yin 29 7 0 01 Apr 2024
Unveiling Vulnerabilities of Contrastive Recommender Systems to Poisoning Attacks Zongwei Wang Junliang Yu Min Gao Hongzhi Yin Bin Cui S. Sadiq AAML 26 7 0 30 Nov 2023
A Survey on Vulnerability of Federated Learning: A Learning Algorithm Perspective Xianghua Xie Chen Hu Hanchi Ren Jingjing Deng FedML AAML 29 19 0 27 Nov 2023
A Survey of Trustworthy Federated Learning with Perspectives on Security, Robustness, and Privacy Yifei Zhang Dun Zeng Jinglong Luo Zenglin Xu Irwin King FedML 84 47 0 21 Feb 2023
A Survey on Federated Recommendation Systems Zehua Sun Yonghui Xu Y. Liu Weiliang He Lanju Kong Fangzhao Wu Y. Jiang Li-zhen Cui FedML 24 60 0 27 Dec 2022
Emerging Trends in Federated Learning: From Model Fusion to Federated X Learning Shaoxiong Ji Yue Tan Teemu Saravirta Zhiqin Yang Yixin Liu Lauri Vasankari Shirui Pan Guodong Long A. Walid FedML 37 76 0 25 Feb 2021