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Model Poisoning

Papers

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Showing 76–100 of 108 papers

TitleStatusHype
Trojan Horse Hunt in Time Series Forecasting for Space Operations—0
Two Heads Are Better than One: Model-Weight and Latent-Space Analysis for Federated Learning on Non-iid Data against Poisoning Attacks—0
Untargeted Poisoning Attack Detection in Federated Learning via Behavior Attestation—0
VerifBFL: Leveraging zk-SNARKs for A Verifiable Blockchained Federated Learning—0
Mitigating Malicious Attacks in Federated Learning via Confidence-aware Defense—0
You Autocomplete Me: Poisoning Vulnerabilities in Neural Code Completion—0
2CP: Decentralized Protocols to Transparently Evaluate Contributivity in Blockchain Federated Learning Environments—0
Protecting Federated Learning from Extreme Model Poisoning Attacks via Multidimensional Time Series Anomaly Detection—0
ACE: A Model Poisoning Attack on Contribution Evaluation Methods in Federated Learning—0
A Client-level Assessment of Collaborative Backdoor Poisoning in Non-IID Federated Learning—0
A First Order Meta Stackelberg Method for Robust Federated Learning—0
Resilience in Online Federated Learning: Mitigating Model-Poisoning Attacks via Partial Sharing—0
An Analysis of Untargeted Poisoning Attack and Defense Methods for Federated Online Learning to Rank Systems—0
Anticipatory Thinking Challenges in Open Worlds: Risk Management—0
A Streamlit-based Artificial Intelligence Trust Platform for Next-Generation Wireless Networks—0
A Synergetic Attack against Neural Network Classifiers combining Backdoor and Adversarial Examples—0
Backdoor Attacks in Federated Learning by Rare Embeddings and Gradient Ensembling—0
BaFFLe: Backdoor detection via Feedback-based Federated Learning—0
CADeSH: Collaborative Anomaly Detection for Smart Homes—0
Can We Trust the Similarity Measurement in Federated Learning?—0
CATFL: Certificateless Authentication-based Trustworthy Federated Learning for 6G Semantic Communications—0
Concealing Backdoor Model Updates in Federated Learning by Trigger-Optimized Data Poisoning—0
Turning Federated Learning Systems Into Covert Channels—0
Covert Model Poisoning Against Federated Learning: Algorithm Design and Optimization—0
Data-Agnostic Model Poisoning against Federated Learning: A Graph Autoencoder Approach—0
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