A Privacy-Preserving Learning Framework for Face Recognition in Edge and Cloud Networks
Offloading the computationally intensive workloads to the edge and cloud not only improves the quality of computation, but also creates an extra degree of diversity by collecting information from devices in service. Nevertheless, significant concerns on privacy are raised as the aggregated informati...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2020-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9146141/ |