Name
Abstract | ||
|---|---|---|
Data security has become the focus of public concern in widely used Deep Learning (DL) applications. Existing attacks can accurately recover any input entered the models. Therefore, it is of the same importance to protect DL models as well as data. Although service providers may offer Trusted Execution Environment (TEE) such as Trusted Software Guard eXtensions (SGX) for model security. The additi... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/IC-NIDC54101.2021.9660566 | 2021 7th IEEE International Conference on Network Intelligence and Digital Content (IC-NIDC) |
Keywords | DocType | ISBN |
Deep learning,Privacy,Costs,Heuristic algorithms,Computational modeling,Data security,Inference algorithms | Conference | 978-1-6654-0582-9 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xuaner Wu | 1 | 0 | 0.34 |
| Konglin Zhu | 2 | 0 | 1.01 |
| Yuyang Peng | 3 | 24 | 4.19 |
| Lin Zhang | 4 | 0 | 1.01 |