KDk: A Defense Mechanism Against Label Inference Attacks in Vertical Federated Learning
Fuente:
arXiv
Saved in:
| Main Authors: | Arazzi, Marco, Nicolazzo, Serena, Nocera, Antonino |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
A Novel IoT Trust Model Leveraging Fully Distributed Behavioral Fingerprinting and Secure Delegation
by: Arazzi, Marco, et al.
Published: (2023)
by: Arazzi, Marco, et al.
Published: (2023)
Label Inference Attacks against Node-level Vertical Federated GNNs
by: Arazzi, Marco, et al.
Published: (2023)
by: Arazzi, Marco, et al.
Published: (2023)
A Deep Reinforcement Learning Approach for Security-Aware Service Acquisition in IoT
by: Arazzi, Marco, et al.
Published: (2024)
by: Arazzi, Marco, et al.
Published: (2024)
Let's Focus: Focused Backdoor Attack against Federated Transfer Learning
by: Arazzi, Marco, et al.
Published: (2024)
by: Arazzi, Marco, et al.
Published: (2024)
Secure Federated Data Distillation
by: Arazzi, Marco, et al.
Published: (2025)
by: Arazzi, Marco, et al.
Published: (2025)
Towards Certified Malware Detection: Provable Guarantees Against Evasion Attacks
by: Giri, Nandakrishna, et al.
Published: (2026)
by: Giri, Nandakrishna, et al.
Published: (2026)
GShield: Mitigating Poisoning Attacks in Federated Learning
by: M., Sameera K., et al.
Published: (2025)
by: M., Sameera K., et al.
Published: (2025)
Privacy Preserving and Robust Aggregation for Cross-Silo Federated Learning in Non-IID Settings
by: Arazzi, Marco, et al.
Published: (2025)
by: Arazzi, Marco, et al.
Published: (2025)
Privacy-Preserving in Blockchain-based Federated Learning Systems
by: M., Sameera K., et al.
Published: (2024)
by: M., Sameera K., et al.
Published: (2024)
Subject Data Auditing via Source Inference Attack in Cross-Silo Federated Learning
by: Li, Jiaxin, et al.
Published: (2024)
by: Li, Jiaxin, et al.
Published: (2024)
When Forgetting Triggers Backdoors: A Clean Unlearning Attack
by: Arazzi, Marco, et al.
Published: (2025)
by: Arazzi, Marco, et al.
Published: (2025)
SecureBreak -- A dataset towards safe and secure models
by: Arazzi, Marco, et al.
Published: (2026)
by: Arazzi, Marco, et al.
Published: (2026)
XBreaking: Understanding how LLMs security alignment can be broken
by: Arazzi, Marco, et al.
Published: (2025)
by: Arazzi, Marco, et al.
Published: (2025)
How Secure is Forgetting? Linking Machine Unlearning to Machine Learning Attacks
by: P., Muhammed Shafi K., et al.
Published: (2025)
by: P., Muhammed Shafi K., et al.
Published: (2025)
LoRA as Oracle
by: Arazzi, Marco, et al.
Published: (2026)
by: Arazzi, Marco, et al.
Published: (2026)
Revisiting Label Inference Attacks in Vertical Federated Learning: Why They Are Vulnerable and How to Defend
by: Liu, Yige, et al.
Published: (2026)
by: Liu, Yige, et al.
Published: (2026)
Privacy Against Agnostic Inference Attacks in Vertical Federated Learning
by: Varasteh, Morteza
Published: (2023)
by: Varasteh, Morteza
Published: (2023)
Service Level Agreements and Security SLA: A Comprehensive Survey
by: Nicolazzo, Serena, et al.
Published: (2024)
by: Nicolazzo, Serena, et al.
Published: (2024)
DroidTTP: Mapping Android Applications with TTP for Cyber Threat Intelligence
by: Arikkat, Dincy R, et al.
Published: (2025)
by: Arikkat, Dincy R, et al.
Published: (2025)
HashVFL: Defending Against Data Reconstruction Attacks in Vertical Federated Learning
by: Qiu, Pengyu, et al.
Published: (2022)
by: Qiu, Pengyu, et al.
Published: (2022)
Exploiting Defenses against GAN-Based Feature Inference Attacks in Federated Learning
by: Luo, Xinjian, et al.
Published: (2020)
by: Luo, Xinjian, et al.
Published: (2020)
FedMID: A Data-Free Method for Using Intermediate Outputs as a Defense Mechanism Against Poisoning Attacks in Federated Learning
by: Han, Sungwon, et al.
Published: (2024)
by: Han, Sungwon, et al.
Published: (2024)
SD-RAG: A Prompt-Injection-Resilient Framework for Selective Disclosure in Retrieval-Augmented Generation
by: Masoud, Aiman Al, et al.
Published: (2026)
by: Masoud, Aiman Al, et al.
Published: (2026)
How to Defend Against Large-scale Model Poisoning Attacks in Federated Learning: A Vertical Solution
by: Wang, Jinbo, et al.
Published: (2024)
by: Wang, Jinbo, et al.
Published: (2024)
Auditing Privacy Mechanisms via Label Inference Attacks
by: Busa-Fekete, Róbert István, et al.
Published: (2024)
by: Busa-Fekete, Róbert István, et al.
Published: (2024)
SecureLearn -- An Attack-agnostic Defense for Multiclass Machine Learning Against Data Poisoning Attacks
by: Paracha, Anum, et al.
Published: (2025)
by: Paracha, Anum, et al.
Published: (2025)
MixNN: Protection of Federated Learning Against Inference Attacks by Mixing Neural Network Layers
by: Boutet, Antoine, et al.
Published: (2021)
by: Boutet, Antoine, et al.
Published: (2021)
EC-LDA : Label Distribution Inference Attack against Federated Graph Learning with Embedding Compression
by: Cheng, Tong, et al.
Published: (2025)
by: Cheng, Tong, et al.
Published: (2025)
PECAN: A Deterministic Certified Defense Against Backdoor Attacks
by: Zhang, Yuhao, et al.
Published: (2023)
by: Zhang, Yuhao, et al.
Published: (2023)
Uncovering Attacks and Defenses in Secure Aggregation for Federated Deep Learning
by: Zhang, Yiwei, et al.
Published: (2024)
by: Zhang, Yiwei, et al.
Published: (2024)
Cooperative Decentralized Backdoor Attacks on Vertical Federated Learning
by: Lee, Seohyun, et al.
Published: (2025)
by: Lee, Seohyun, et al.
Published: (2025)
A No-Defense Defense Against Gradient-Based Adversarial Attacks on ML-NIDS: Is Less More?
by: elShehaby, Mohamed, et al.
Published: (2026)
by: elShehaby, Mohamed, et al.
Published: (2026)
Rethinking Membership Inference Attacks Against Transfer Learning
by: Wu, Cong, et al.
Published: (2025)
by: Wu, Cong, et al.
Published: (2025)
LabObf: A Label Protection Scheme for Vertical Federated Learning Through Label Obfuscation
by: He, Ying, et al.
Published: (2024)
by: He, Ying, et al.
Published: (2024)
Security in LLM-as-a-Judge: A Comprehensive SoK
by: Masoud, Aiman Al, et al.
Published: (2026)
by: Masoud, Aiman Al, et al.
Published: (2026)
URVFL: Undetectable Data Reconstruction Attack on Vertical Federated Learning
by: Yao, Duanyi, et al.
Published: (2024)
by: Yao, Duanyi, et al.
Published: (2024)
Dashed Line Defense: Plug-And-Play Defense Against Adaptive Score-Based Query Attacks
by: Fu, Yanzhang, et al.
Published: (2026)
by: Fu, Yanzhang, et al.
Published: (2026)
Adaptive Attacks Break Defenses Against Indirect Prompt Injection Attacks on LLM Agents
by: Zhan, Qiusi, et al.
Published: (2025)
by: Zhan, Qiusi, et al.
Published: (2025)
A New Federated Learning Framework Against Gradient Inversion Attacks
by: Guo, Pengxin, et al.
Published: (2024)
by: Guo, Pengxin, et al.
Published: (2024)
A Multi-Agent LLM Defense Pipeline Against Prompt Injection Attacks
by: Hossain, S M Asif, et al.
Published: (2025)
by: Hossain, S M Asif, et al.
Published: (2025)
Similar Items
-
A Novel IoT Trust Model Leveraging Fully Distributed Behavioral Fingerprinting and Secure Delegation
by: Arazzi, Marco, et al.
Published: (2023) -
Label Inference Attacks against Node-level Vertical Federated GNNs
by: Arazzi, Marco, et al.
Published: (2023) -
A Deep Reinforcement Learning Approach for Security-Aware Service Acquisition in IoT
by: Arazzi, Marco, et al.
Published: (2024) -
Let's Focus: Focused Backdoor Attack against Federated Transfer Learning
by: Arazzi, Marco, et al.
Published: (2024) -
Secure Federated Data Distillation
by: Arazzi, Marco, et al.
Published: (2025)