Dynamic Edge-Based High-Dimensional Data Aggregation with Differential Privacy
Qian Chen,
Zhiwei Ni,
Xuhui Zhu
et al.
Abstract:Edge computing enables efficient data aggregation for services like data sharing and analysis in distributed IoT applications. However, uploading dynamic high-dimensional data to an edge server for efficient aggregation is challenging. Additionally, there is the significant risk of privacy leakage associated with direct such data uploading. Therefore, we propose an edge-based differential privacy data aggregation method leveraging progressive UMAP with a dynamic time window based on LSTM (EDP-PUDL). Firstly, a… Show more
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