Imagen de Portada

Privacy-Preserving in Blockchain-based Federated Learning Systems

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	M., Sameera K., Nicolazzo, Serena, Arazzi, Marco, Nocera, Antonino, A., Rafidha Rehiman K., P, Vinod, Conti, Mauro
Formato:	Preprint
Publicado:	2024
Materias:	Cryptography and Security Artificial Intelligence Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

GShield: Mitigating Poisoning Attacks in Federated Learning
por: M., Sameera K., et al.
Publicado: (2025)

A Deep Reinforcement Learning Approach for Security-Aware Service Acquisition in IoT
por: Arazzi, Marco, et al.
Publicado: (2024)

WeiDetect: Weibull Distribution-Based Defense against Poisoning Attacks in Federated Learning for Network Intrusion Detection Systems
por: M., Sameera K., et al.
Publicado: (2025)

DroidTTP: Mapping Android Applications with TTP for Cyber Threat Intelligence
por: Arikkat, Dincy R, et al.
Publicado: (2025)

Secure Federated Data Distillation
por: Arazzi, Marco, et al.
Publicado: (2025)

Subject Data Auditing via Source Inference Attack in Cross-Silo Federated Learning
por: Li, Jiaxin, et al.
Publicado: (2024)

CTI Dataset Construction from Telegram
por: Arikkat, Dincy R., et al.
Publicado: (2025)

Privacy Preserving and Robust Aggregation for Cross-Silo Federated Learning in Non-IID Settings
por: Arazzi, Marco, et al.
Publicado: (2025)

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

SeCTIS: A Framework to Secure CTI Sharing
por: Arikkat, Dincy R., et al.
Publicado: (2024)

A Novel IoT Trust Model Leveraging Fully Distributed Behavioral Fingerprinting and Secure Delegation
por: Arazzi, Marco, et al.
Publicado: (2023)

Security through the Eyes of AI: How Visualization is Shaping Malware Detection
por: Brosolo, Matteo, et al.
Publicado: (2025)

LoRA as Oracle
por: Arazzi, Marco, et al.
Publicado: (2026)

Enhancing Android Malware Detection with Retrieval-Augmented Generation
por: S., Saraga, et al.
Publicado: (2025)

Security in LLM-as-a-Judge: A Comprehensive SoK
por: Masoud, Aiman Al, et al.
Publicado: (2026)

XBreaking: Understanding how LLMs security alignment can be broken
por: Arazzi, Marco, et al.
Publicado: (2025)

SD-RAG: A Prompt-Injection-Resilient Framework for Selective Disclosure in Retrieval-Augmented Generation
por: Masoud, Aiman Al, et al.
Publicado: (2026)

When Forgetting Triggers Backdoors: A Clean Unlearning Attack
por: Arazzi, Marco, et al.
Publicado: (2025)

How Secure is Forgetting? Linking Machine Unlearning to Machine Learning Attacks
por: P., Muhammed Shafi K., et al.
Publicado: (2025)

Protecting Deep Neural Network Intellectual Property with Chaos-Based White-Box Watermarking
por: B, Sangeeth, et al.
Publicado: (2025)

SecureBreak -- A dataset towards safe and secure models
por: Arazzi, Marco, et al.
Publicado: (2026)

Deep Learning Fusion For Effective Malware Detection: Leveraging Visual Features
por: Johny, Jahez Abraham, et al.
Publicado: (2024)

Towards Certified Malware Detection: Provable Guarantees Against Evasion Attacks
por: Giri, Nandakrishna, et al.
Publicado: (2026)

Let's Focus: Focused Backdoor Attack against Federated Transfer Learning
por: Arazzi, Marco, et al.
Publicado: (2024)

Discerning Reliable Cyber Threat Indicators for Timely Cyber Threat Intelligence
por: Arikkat, Dincy R, et al.
Publicado: (2023)

Service Level Agreements and Security SLA: A Comprehensive Survey
por: Nicolazzo, Serena, et al.
Publicado: (2024)

Label Inference Attacks against Node-level Vertical Federated GNNs
por: Arazzi, Marco, et al.
Publicado: (2023)

PPBFL: A Privacy Protected Blockchain-based Federated Learning Model
por: Li, Yang, et al.
Publicado: (2024)

MoRSE: Bridging the Gap in Cybersecurity Expertise with Retrieval Augmented Generation
por: Simoni, Marco, et al.
Publicado: (2024)

SoK: The Last Line of Defense: On Backdoor Defense Evaluation
por: Abad, Gorka, et al.
Publicado: (2025)

Privacy Preserving Federated Learning with Convolutional Variational Bottlenecks
por: Scheliga, Daniel, et al.
Publicado: (2023)

Privacy-Preserving Decentralized Federated Learning via Explainable Adaptive Differential Privacy
por: Piran, Fardin Jalil, et al.
Publicado: (2025)

BF-Meta: Secure Blockchain-enhanced Privacy-preserving Federated Learning for Metaverse
por: Liu, Wenbo, et al.
Publicado: (2024)

Membership Privacy Evaluation in Deep Spiking Neural Networks
por: Li, Jiaxin, et al.
Publicado: (2024)

TAPFed: Threshold Secure Aggregation for Privacy-Preserving Federated Learning
por: Xu, Runhua, et al.
Publicado: (2025)

Privacy Preserving Machine Learning Workflow: from Anonymization to Personalized Differential Privacy Budgets in Federated Learning
por: Díaz, Judith Sáinz-Pardo, et al.
Publicado: (2026)

FedAdOb: Privacy-Preserving Federated Deep Learning with Adaptive Obfuscation
por: Gu, Hanlin, et al.
Publicado: (2024)

Deciphering the Interplay between Attack and Protection Complexity in Privacy-Preserving Federated Learning
por: Zhang, Xiaojin, et al.
Publicado: (2025)

A Privacy-Preserving Federated Learning Method with Homomorphic Encryption in Omics Data
por: Negoya, Yusaku, et al.
Publicado: (2025)

Zero-Knowledge Federated Learning: A New Trustworthy and Privacy-Preserving Distributed Learning Paradigm
por: Wang, Taotao, et al.
Publicado: (2025)