Image de couverture de livre

MAGNETO: Edge AI for Human Activity Recognition -- Privacy and Personalization

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Zuo, Jingwei, Arvanitakis, George, Ndhlovu, Mthandazo, Hacid, Hakim
Format:	Preprint
Publié:	2024
Sujets:	Machine Learning Artificial Intelligence Cryptography and Security
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Federated Split Learning for Human Activity Recognition with Differential Privacy
par: Ndeko, Josue, et autres
Publié: (2024)

Trustworthy Intrusion Detection: Confidence Estimation Using Latent Space
par: Pitsiorlas, Ioannis, et autres
Publié: (2024)

GOD model: Privacy Preserved AI School for Personal Assistant
par: PIN AI Team, et autres
Publié: (2025)

AI-Driven Anonymization: Protecting Personal Data Privacy While Leveraging Machine Learning
par: Yang, Le, et autres
Publié: (2024)

Revolutionizing Cyber Threat Detection with Large Language Models: A privacy-preserving BERT-based Lightweight Model for IoT/IIoT Devices
par: Ferrag, Mohamed Amine, et autres
Publié: (2023)

Privacy Assessment of Federated Learning using Private Personalized Layers
par: Jourdan, Théo, et autres
Publié: (2021)

Cross-silo Federated Learning with Record-level Personalized Differential Privacy
par: Liu, Junxu, et autres
Publié: (2024)

Privacy-Utility Trade-off in Data Publication: A Bilevel Optimization Framework with Curvature-Guided Perturbation
par: Yin, Yi, et autres
Publié: (2025)

Protecting Activity Sensing Data Privacy Using Hierarchical Information Dissociation
par: Wang, Guangjing, et autres
Publié: (2024)

Inducing Uncertainty on Open-Weight Models for Test-Time Privacy in Image Recognition
par: Ashiq, Muhammad H., et autres
Publié: (2025)

SoK: Security and Privacy Risks of Healthcare AI
par: Chang, Yuanhaur, et autres
Publié: (2024)

Privacy Implications of Explainable AI in Data-Driven Systems
par: Ezzeddine, Fatima
Publié: (2024)

Client Clustering Meets Knowledge Sharing: Enhancing Privacy and Robustness in Personalized Peer-to-Peer Learning
par: Maheri, Mohammad Mahdi, et autres
Publié: (2025)

Privacy and Security Implications of Cloud-Based AI Services : A Survey
par: Luqman, Alka, et autres
Publié: (2024)

A Human-Centered Privacy Approach (HCP) to AI
par: Sun, Luyi, et autres
Publié: (2026)

Robust Privacy: Inference-Time Privacy through Certified Robustness
par: Jin, Jiankai, et autres
Publié: (2026)

RAVEN: Retrieval-Augmented Vulnerability Exploration Network for Memory Corruption Analysis in User Code and Binary Programs
par: Jamwal, Parteek, et autres
Publié: (2026)

Beyond Data Privacy: New Privacy Risks for Large Language Models
par: Du, Yuntao, et autres
Publié: (2025)

Your Privacy Depends on Others: Collusion Vulnerabilities in Individual Differential Privacy
par: Kaiser, Johannes, et autres
Publié: (2026)

Re-thinking Human Activity Recognition with Hierarchy-aware Label Relationship Modeling
par: Zuo, Jingwei, et autres
Publié: (2024)

RAG with Differential Privacy
par: Grislain, Nicolas
Publié: (2024)

How to make Medical AI Systems safer? Simulating Vulnerabilities, and Threats in Multimodal Medical RAG System
par: Zuo, Kaiwen, et autres
Publié: (2025)

The Inadequacy of Similarity-based Privacy Metrics: Privacy Attacks against "Truly Anonymous" Synthetic Datasets
par: Ganev, Georgi, et autres
Publié: (2023)

Privacy-Preserving Dynamic Assortment Selection
par: Cho, Young Hyun, et autres
Publié: (2024)

Evaluating Privacy Leakage in Split Learning
par: Qiu, Xinchi, et autres
Publié: (2023)

Privacy Auditing of Large Language Models
par: Panda, Ashwinee, et autres
Publié: (2025)

When Fairness Meets Privacy: Exploring Privacy Threats in Fair Binary Classifiers via Membership Inference Attacks
par: Tian, Huan, et autres
Publié: (2023)

Provable Privacy with Non-Private Pre-Processing
par: Hu, Yaxi, et autres
Publié: (2024)

Bridging Privacy and Robustness for Trustworthy Machine Learning
par: Zhang, Xiaojin, et autres
Publié: (2024)

Unveiling Privacy, Memorization, and Input Curvature Links
par: Ravikumar, Deepak, et autres
Publié: (2024)

Tight Auditing of Differential Privacy in MST and AIM
par: Ganev, Georgi, et autres
Publié: (2026)

Unlink to Unlearn: Simplifying Edge Unlearning in GNNs
par: Tan, Jiajun, et autres
Publié: (2024)

How Does a Deep Learning Model Architecture Impact Its Privacy? A Comprehensive Study of Privacy Attacks on CNNs and Transformers
par: Zhang, Guangsheng, et autres
Publié: (2022)

Privacy-Preserving in Blockchain-based Federated Learning Systems
par: M., Sameera K., et autres
Publié: (2024)

Near-Optimal Reinforcement Learning with Shuffle Differential Privacy
par: Bai, Shaojie, et autres
Publié: (2024)

Decentralized Federated Learning: A Survey on Security and Privacy
par: Hallaji, Ehsan, et autres
Publié: (2024)

Differential Privacy Mechanisms in Neural Tangent Kernel Regression
par: Gu, Jiuxiang, et autres
Publié: (2024)

RL-Finetuned LLMs for Privacy-Preserving Synthetic Rewriting
par: Shi, Zhan, et autres
Publié: (2025)

Mind the Gap: Mixtures of Gaussians in Approximate Differential Privacy
par: Liu, Huikang, et autres
Publié: (2026)

Decoupling Generalizability and Membership Privacy Risks in Neural Networks
par: Fang, Xingli, et autres
Publié: (2026)