Cover Image

Privacy-Preserving Machine Learning for IoT: A Cross-Paradigm Survey and Future Roadmap

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zaman, Zakia, Gauravaram, Praveen, Hassan, Mahbub, Jha, Sanjay, Hu, Wen
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Cryptography and Security
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Privacy-Preserving Distributed Learning in IoT Systems: A Unified Threat Model and Evaluation Framework
by: Cartmell, John, et al.
Published: (2026)

Agentic Privacy-Preserving Machine Learning
by: Zhang, Mengyu, et al.
Published: (2025)

Optimized IoT Intrusion Detection using Machine Learning Technique
by: Mahmud, Muhammad Zawad, et al.
Published: (2024)

A Novel Ensemble Learning Approach for Enhanced IoT Attack Detection: Redefining Security Paradigms in Connected Systems
by: Abdeljaber, Hikmat A. M., et al.
Published: (2025)

Secure and Privacy-Preserving Federated Learning for Next-Generation Underground Mine Safety
by: Elmahallawy, Mohamed, et al.
Published: (2025)

Towards Efficient Machine Learning Method for IoT DDoS Attack Detection
by: Modi, P
Published: (2024)

A Lightweight Federated Learning Approach for Privacy-Preserving Botnet Detection in IoT
by: Mahmoud, Taha M., et al.
Published: (2025)

A Comparative Analysis of Machine Learning Models for DDoS Detection in IoT Networks
by: Shakya, Sushil, et al.
Published: (2024)

Analyzing Consumer IoT Traffic from Security and Privacy Perspectives: a Comprehensive Survey
by: Jia, Yan, et al.
Published: (2024)

Federated Learning-Driven Cybersecurity Framework for IoT Networks with Privacy-Preserving and Real-Time Threat Detection Capabilities
by: Rahmati, Milad
Published: (2025)

Privacy Preserving Machine Learning Model Personalization through Federated Personalized Learning
by: Hosain, Md. Tanzib, et al.
Published: (2025)

Secure Sparse Matrix Multiplications and their Applications to Privacy-Preserving Machine Learning
by: Damie, Marc, et al.
Published: (2025)

Privacy Preservation through Practical Machine Unlearning
by: Dilworth, Robert
Published: (2025)

Privacy-Preserving Generative Models: A Comprehensive Survey
by: Padariya, Debalina, et al.
Published: (2025)

SSNet: A Lightweight Multi-Party Computation Scheme for Practical Privacy-Preserving Machine Learning Service in the Cloud
by: Duan, Shijin, et al.
Published: (2024)

A Novel Review of Stability Techniques for Improved Privacy-Preserving Machine Learning
by: DuPlessie, Coleman, et al.
Published: (2024)

The Normal Distributions Indistinguishability Spectrum and its Application to Privacy-Preserving Machine Learning
by: Wei, Yu, et al.
Published: (2023)

SFPDML: Securer and Faster Privacy-Preserving Distributed Machine Learning based on MKTFHE
by: Wang, Hongxiao, et al.
Published: (2022)

Systematic Survey on Privacy-Preserving Architectures for IoT and Vehicular Data Sharing: Techniques, Challenges, and Future Directions
by: Tran-Truong, Phat T., et al.
Published: (2026)

SoK: Privacy Preserving Machine Learning using Functional Encryption: Opportunities and Challenges
by: Panzade, Prajwal, et al.
Published: (2022)

Preserving Privacy and Security in Federated Learning
by: Nguyen, Truc, et al.
Published: (2022)

A Blockchain Solution for Collaborative Machine Learning over IoT
by: Beis-Penedo, Carlos, et al.
Published: (2023)

GuardML: Efficient Privacy-Preserving Machine Learning Services Through Hybrid Homomorphic Encryption
by: Frimpong, Eugene, et al.
Published: (2024)

Comparison of Fully Homomorphic Encryption and Garbled Circuit Techniques in Privacy-Preserving Machine Learning Inference
by: Cheerla, Kalyan, et al.
Published: (2025)

Hawk: Accurate and Fast Privacy-Preserving Machine Learning Using Secure Lookup Table Computation
by: Saleem, Hamza, et al.
Published: (2024)

SunBlock: Cloudless Protection for IoT Systems
by: Safronov, Vadim, et al.
Published: (2024)

Privacy Preserving Reinforcement Learning for Population Processes
by: Yang-Zhao, Samuel, et al.
Published: (2024)

Enhancing Cybersecurity in IoT Networks: A Deep Learning Approach to Anomaly Detection
by: Pang, Yining, et al.
Published: (2024)

Adaptive Intrusion Detection for Evolving RPL IoT Attacks Using Incremental Learning
by: Bas, Sumeyye, et al.
Published: (2025)

Preempting Text Sanitization Utility in Resource-Constrained Privacy-Preserving LLM Interactions
by: Carpentier, Robin, et al.
Published: (2024)

Privacy Preserving In-Context-Learning Framework for Large Language Models
by: Bhusal, Bishnu, et al.
Published: (2025)

Privacy-Preserving Graph-Based Machine Learning with Fully Homomorphic Encryption for Collaborative Anti-Money Laundering
by: Effendi, Fabrianne, et al.
Published: (2024)

Privacy Preserving Machine Learning for Electronic Health Records using Federated Learning and Differential Privacy
by: Ganadily, Naif A., et al.
Published: (2024)

Effectiveness of L2 Regularization in Privacy-Preserving Machine Learning
by: Chandrinos, Nikolaos, et al.
Published: (2024)

Harnessing Inherent Noises for Privacy Preservation in Quantum Machine Learning
by: Ju, Keyi, et al.
Published: (2023)

In-network Attack Detection with Federated Deep Learning in IoT Networks: Real Implementation and Analysis
by: Chaudhary, Devashish, et al.
Published: (2026)

Automated Privacy-Preserving Techniques via Meta-Learning
by: Carvalho, Tânia, et al.
Published: (2024)

Preserving Expert-Level Privacy in Offline Reinforcement Learning
by: Sharma, Navodita, et al.
Published: (2024)

Privacy Preservation Techniques (PPTs) in IoT Systems: A Scoping Review and Future Directions
by: Alalade, Emmanuel, et al.
Published: (2025)

A Privacy-Preserving Framework for Advertising Personalization Incorporating Federated Learning and Differential Privacy
by: Li, Xiang, et al.
Published: (2025)