Copertina

Federated Learning: Attacks, Defenses, Opportunities, and Challenges

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Shirvani, Ghazaleh, Ghasemshirazi, Saeid, Beigzadeh, Behzad
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Cryptography and Security
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Powering the Future of IoT: Federated Learning for Optimized Power Consumption and Enhanced Privacy
di: Shirvani, Ghazaleh, et al.
Pubblicazione: (2024)

Towards Sustainable IoT: Challenges, Solutions, and Future Directions for Device Longevity
di: Shirvani, Ghazaleh, et al.
Pubblicazione: (2024)

Enhancing IoT Security Against DDoS Attacks through Federated Learning
di: Shirvani, Ghazaleh, et al.
Pubblicazione: (2024)

Securing the Future: Proactive Threat Hunting for Sustainable IoT Ecosystems
di: Ghasemshirazi, Saeid, et al.
Pubblicazione: (2024)

Advancing Email Spam Detection: Leveraging Zero-Shot Learning and Large Language Models
di: SHirvani, Ghazaleh, et al.
Pubblicazione: (2025)

Implementing Zero Trust Architecture to Enhance Security and Resilience in the Pharmaceutical Supply Chain
di: Ghasemshirazi, Saeid, et al.
Pubblicazione: (2025)

Membership Inference Attacks and Defenses in Federated Learning: A Survey
di: Bai, Li, et al.
Pubblicazione: (2024)

Distributed Backdoor Attacks on Federated Graph Learning and Certified Defenses
di: Yang, Yuxin, et al.
Pubblicazione: (2024)

A Learning-Based Attack Framework to Break SOTA Poisoning Defenses in Federated Learning
di: Yang, Yuxin, et al.
Pubblicazione: (2024)

FedSecurity: Benchmarking Attacks and Defenses in Federated Learning and Federated LLMs
di: Han, Shanshan, et al.
Pubblicazione: (2023)

Adversarial Machine Learning: Attacks, Defenses, and Open Challenges
di: Jha, Pranav K
Pubblicazione: (2025)

Hybrid Reputation Aggregation: A Robust Defense Mechanism for Adversarial Federated Learning in 5G and Edge Network Environments
di: Sheikhi, Saeid, et al.
Pubblicazione: (2025)

Uncovering Attacks and Defenses in Secure Aggregation for Federated Deep Learning
di: Zhang, Yiwei, et al.
Pubblicazione: (2024)

AntiFLipper: A Secure and Efficient Defense Against Label-Flipping Attacks in Federated Learning
di: Rahman, Aashnan, et al.
Pubblicazione: (2025)

Dual Defense: Enhancing Privacy and Mitigating Poisoning Attacks in Federated Learning
di: Xu, Runhua, et al.
Pubblicazione: (2025)

I Know What You Sync: Covert and Side Channel Attacks on File Systems via syncfs
di: Gu, Cheng, et al.
Pubblicazione: (2024)

Quantum Adversarial Machine Learning and Defense Strategies: Challenges and Opportunities
di: Yocam, Eric, et al.
Pubblicazione: (2024)

Multi-Agent LLM Governance for Safe Two-Timescale Reinforcement Learning in SDN-IoT Defense
di: Jamshidi, Saeid, et al.
Pubblicazione: (2026)

Exploiting Defenses against GAN-Based Feature Inference Attacks in Federated Learning
di: Luo, Xinjian, et al.
Pubblicazione: (2020)

A Comprehensive Survey of Website Fingerprinting Attacks and Defenses in Tor: Advances and Open Challenges
di: Cui, Yuwen, et al.
Pubblicazione: (2025)

KDk: A Defense Mechanism Against Label Inference Attacks in Vertical Federated Learning
di: Arazzi, Marco, et al.
Pubblicazione: (2024)

SoK: Benchmarking Poisoning Attacks and Defenses in Federated Learning
di: Zhang, Heyi, et al.
Pubblicazione: (2025)

Defense Against Prompt Injection Attack by Leveraging Attack Techniques
di: Chen, Yulin, et al.
Pubblicazione: (2024)

Deep Learning Model Inversion Attacks and Defenses: A Comprehensive Survey
di: Yang, Wencheng, et al.
Pubblicazione: (2025)

Siren Song: Manipulating Pose Estimation in XR Headsets Using Acoustic Attacks
di: Huang, Zijian, et al.
Pubblicazione: (2025)

A Data-Driven Defense against Edge-case Model Poisoning Attacks on Federated Learning
di: Purohit, Kiran, et al.
Pubblicazione: (2023)

System Password Security: Attack and Defense Mechanisms
di: Shi, Chaofang, et al.
Pubblicazione: (2025)

Defensive Prompt Patch: A Robust and Interpretable Defense of LLMs against Jailbreak Attacks
di: Xiong, Chen, et al.
Pubblicazione: (2024)

United We Defend: Collaborative Membership Inference Defenses in Federated Learning
di: Bai, Li, et al.
Pubblicazione: (2026)

BDPFL: Backdoor Defense for Personalized Federated Learning via Explainable Distillation
di: Zhu, Chengcheng, et al.
Pubblicazione: (2025)

A Taxonomy of Attacks and Defenses in Split Learning
di: Shabbir, Aqsa, et al.
Pubblicazione: (2025)

That Doesn't Go There: Attacks on Shared State in Multi-User Augmented Reality Applications
di: Slocum, Carter, et al.
Pubblicazione: (2023)

Open Source, Open Threats? Investigating Security Challenges in Open-Source Software
di: Akhavani, Seyed Ali, et al.
Pubblicazione: (2025)

Attack and Defense of Deep Learning Models in the Field of Web Attack Detection
di: Shi, Lijia, et al.
Pubblicazione: (2024)

ICL-EVADER: Zero-Query Black-Box Evasion Attacks on In-Context Learning and Their Defenses
di: He, Ningyuan, et al.
Pubblicazione: (2026)

JNI Global References Are Still Vulnerable: Attacks and Defenses
di: He, Yi, et al.
Pubblicazione: (2024)

An Attack-Driven Incident Response and Defense System (ADIRDS)
di: Lai, Anthony Cheuk Tung, et al.
Pubblicazione: (2025)

Enhanced MLLM Black-Box Jailbreaking Attacks and Defenses
di: Zhong, Xingwei, et al.
Pubblicazione: (2025)

Non-control-Data Attacks and Defenses: A review
di: Chong, Lei
Pubblicazione: (2025)

NVBleed: Covert and Side-Channel Attacks on NVIDIA Multi-GPU Interconnect
di: Zhang, Yicheng, et al.
Pubblicazione: (2025)