AI RESEARCH
Privacy-Preserving Machine Learning for IoT: A Cross-Paradigm Survey and Future Roadmap
arXiv CS.LG
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ArXi:2603.13570v1 Announce Type: new The rapid proliferation of the Internet of Things has intensified demand for robust privacy-preserving machine learning mechanisms to safeguard sensitive data generated by large-scale, heterogeneous, and resource-constrained devices. Unlike centralized environments, IoT ecosystems are inherently decentralized, bandwidth-limited, and latency-sensitive, exposing privacy risks across sensing, communication, and distributed