AIFL: Ensuring Unlinkable Anonymity and Robust Incentive in Cross-Device Federated Learning
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DOI: 10.1109/jiot.2024.3417003
Abstract: While cross-device federated learning (FL) offers a privacy-preserving data processing approach for Internet of Things (IoT) devices, it introduces fresh privacy risks and elevated computational expenses. Current solutions prioritize data privacy, often overlooking identity privacy… read more here.
Keywords: cross device; robust incentive; privacy; unlinkable anonymity ... See more keywords