Image de couverture de livre

Adversarial Robustness Unhardening via Backdoor Attacks in Federated Learning

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Kim, Taejin, Li, Jiarui, Singh, Shubhranshu, Madaan, Nikhil, Joe-Wong, Carlee
Format:	Preprint
Publié:	2023
Sujets:	Machine Learning Artificial Intelligence
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Federated Learning with Flexible Architectures
par: Park, Jong-Ik, et autres
Publié: (2024)

Memory-Based Advantage Shaping for LLM-Guided Reinforcement Learning
par: Nourzad, Narjes, et autres
Publié: (2026)

MIRA: Memory-Integrated Reinforcement Learning Agent with Limited LLM Guidance
par: Nourzad, Narjes, et autres
Publié: (2026)

FedTLU: Federated Learning with Targeted Layer Updates
par: Park, Jong-Ik, et autres
Publié: (2024)

Neural Combinatorial Clustered Bandits for Recommendation Systems
par: Atalar, Baran, et autres
Publié: (2024)

Matrix-Space Reinforcement Learning for Reusing Local Transition Geometry
par: Zhang, Zuyuan, et autres
Publié: (2026)

Robust Federated Learning under Adversarial Attacks via Loss-Based Client Clustering
par: Kritharakis, Emmanouil, et autres
Publié: (2025)

An LLM-Based Digital Twin for Optimizing Human-in-the Loop Systems
par: Yang, Hanqing, et autres
Publié: (2024)

The Five Ws of Multi-Agent Communication: Who Talks to Whom, When, What, and Why -- A Survey from MARL to Emergent Language and LLMs
par: Chen, Jingdi, et autres
Publié: (2026)

Fair Concurrent Training of Multiple Models in Federated Learning
par: Siew, Marie, et autres
Publié: (2024)

FLAT: Latent-Driven Arbitrary-Target Backdoor Attacks in Federated Learning
par: Nguyen, Tuan, et autres
Publié: (2025)

DYNAMITE: Dynamic Interplay of Mini-Batch Size and Aggregation Frequency for Federated Learning with Static and Streaming Dataset
par: Liu, Weijie, et autres
Publié: (2023)

Structure-Aware Distributed Backdoor Attacks in Federated Learning
par: Jian, Wang, et autres
Publié: (2026)

CoRAST: Towards Foundation Model-Powered Correlated Data Analysis in Resource-Constrained CPS and IoT
par: Hu, Yi, et autres
Publié: (2024)

FLAIN: Mitigating Backdoor Attacks in Federated Learning via Flipping Weight Updates of Low-Activation Input Neurons
par: Ding, Binbin, et autres
Publié: (2024)

Exploiting Layer-Specific Vulnerabilities to Backdoor Attack in Federated Learning
par: Foroughi, Mohammad Hadi, et autres
Publié: (2026)

Backdoor Attack on Vertical Federated Graph Neural Network Learning
par: Yang, Jirui, et autres
Publié: (2024)

Client-Side Patching against Backdoor Attacks in Federated Learning
par: Molina-Coronado, Borja
Publié: (2024)

Hide and Find: A Distributed Adversarial Attack on Federated Graph Learning
par: Liu, Jinshan, et autres
Publié: (2026)

DR. WELL: Dynamic Reasoning and Learning with Symbolic World Model for Embodied LLM-Based Multi-Agent Collaboration
par: Nourzad, Narjes, et autres
Publié: (2025)

TACO: Tackling Over-correction in Federated Learning with Tailored Adaptive Correction
par: Liu, Weijie, et autres
Publié: (2025)

The Eminence in Shadow: Exploiting Feature Boundary Ambiguity for Robust Backdoor Attacks
par: Feng, Zhou, et autres
Publié: (2025)

QMOS: Enhancing LLMs for Telecommunication with Question Masked loss and Option Shuffling
par: Guda, Blessed, et autres
Publié: (2024)

Non-Cooperative Backdoor Attacks in Federated Learning: A New Threat Landscape
par: Nguyen, Tuan, et autres
Publié: (2024)

A Vision-Language Pre-training Model-Guided Approach for Mitigating Backdoor Attacks in Federated Learning
par: Gai, Keke, et autres
Publié: (2025)

FedProphet: Memory-Efficient Federated Adversarial Training via Robust and Consistent Cascade Learning
par: Tang, Minxue, et autres
Publié: (2024)

Robust Graph Learning Against Adversarial Evasion Attacks via Prior-Free Diffusion-Based Structure Purification
par: Luo, Jiayi, et autres
Publié: (2025)

GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks
par: Cui, Canyixing, et autres
Publié: (2026)

Defending the Edge: Representative-Attention Defense against Backdoor Attacks in Federated Learning
par: Obioma, Chibueze Peace, et autres
Publié: (2025)

PNAct: Crafting Backdoor Attacks in Safe Reinforcement Learning
par: Guo, Weiran, et autres
Publié: (2025)

Internal Planning in Language Models: Characterizing Horizon and Branch Awareness
par: Ustaomeroglu, Muhammed, et autres
Publié: (2025)

Batch-Size Independent Regret Bounds for Combinatorial Semi-Bandits with Probabilistically Triggered Arms or Independent Arms
par: Liu, Xutong, et autres
Publié: (2022)

Efficient Contextual LLM Cascades through Budget-Constrained Policy Learning
par: Zhang, Xuechen, et autres
Publié: (2024)

How Worst-Case Are Adversarial Attacks? Linking Adversarial and Perturbation Robustness
par: Rossolini, Giulio
Publié: (2026)

Robust Deep Reinforcement Learning Through Adversarial Attacks and Training : A Survey
par: Schott, Lucas, et autres
Publié: (2024)

Cooperative Backdoor Attack in Decentralized Reinforcement Learning with Theoretical Guarantee
par: Gao, Mengtong, et autres
Publié: (2024)

FedDefender: Backdoor Attack Defense in Federated Learning
par: Gill, Waris, et autres
Publié: (2023)

Observation-Free Attacks on Online Learning to Rank
par: Chattopadhyay, Sameep, et autres
Publié: (2025)

Heterogeneous Graph Backdoor Attack
par: Chen, Jiawei, et autres
Publié: (2025)

Unlearn to Relearn Backdoors: Deferred Backdoor Functionality Attacks on Deep Learning Models
par: Shin, Jeongjin, et autres
Publié: (2024)