Data Poisoning Attacks and Defenses to Crowdsourcing Systems

Data Poisoning Attacks and Defenses to Crowdsourcing Systems

18 February 2021

Qi Li

Neil Zhenqiang Gong

Papers citing "Data Poisoning Attacks and Defenses to Crowdsourcing Systems"

7 / 7 papers shown

Title
Robust Decision Aggregation with Adversarial Experts Yongkang Guo Yuqing Kong 35 0 0 13 Mar 2024
Edge Learning for 6G-enabled Internet of Things: A Comprehensive Survey of Vulnerabilities, Datasets, and Defenses M. Ferrag Othmane Friha B. Kantarci Norbert Tihanyi Lucas C. Cordeiro Merouane Debbah Djallel Hamouda Muna Al-Hawawreh K. Choo 25 43 0 17 Jun 2023
XMAM:X-raying Models with A Matrix to Reveal Backdoor Attacks for Federated Learning Jianyi Zhang Fangjiao Zhang Qichao Jin Zhiqiang Wang Xiaodong Lin X. Hei AAML FedML 32 0 0 28 Dec 2022
FairRoad: Achieving Fairness for Recommender Systems with Optimized Antidote Data Minghong Fang Jia-Wei Liu Michinari Momma Yi Sun 30 4 0 13 Dec 2022
PoisonedEncoder: Poisoning the Unlabeled Pre-training Data in Contrastive Learning Hongbin Liu Jinyuan Jia Neil Zhenqiang Gong 25 34 0 13 May 2022
FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping Xiaoyu Cao Minghong Fang Jia Liu Neil Zhenqiang Gong FedML 117 612 0 27 Dec 2020
Analyzing Federated Learning through an Adversarial Lens A. Bhagoji Supriyo Chakraborty Prateek Mittal S. Calo FedML 191 1,032 0 29 Nov 2018