Yang, Zezhang and Li, Jian and Yang, Ping (2021) FedADMP: A Joint Anomaly Detection and Mobility Prediction Framework via Federated Learning. EAI Endorsed Transactions on Security and Safety.
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Abstract
With the proliferation of mobile devices and smart cameras, detecting anomalies and predicting their mobility are critical for enhancing safety in ubiquitous computing systems. Due to data privacy regulations and limited communication bandwidth, it is infeasible to collect, transmit, and store all d
| Item Type: | Article |
|---|---|
| Date Deposited: | 04 Mar 2026 14:52 |
| Last Modified: | 11 Apr 2026 15:53 |
| URI: | http://eprints.eai.eu/id/eprint/36825 |
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