cuSCNN: A Secure and Batch-Processing Framework for Privacy-Preserving Convolutional Neural Network Prediction on GPU.
- DOI
- 10.3389/fncom.2021.799977
- Published
- 2021
- Container
- Frontiers in computational neuroscience
- Publisher
- Not recorded
- Open access
- yes
Credibility signals
limited evidence Score 45/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
Show all credibility signals
- cautionDOI registered: No matching Crossref record was present in this response.
- cautionDOI resolves: No matching Crossref record was present in this response.
- not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility.
- not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made.
- not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made.
- not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made.
- not scoredROR affiliation: Not checked or no result supplied; no credibility inference made.
- not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- supportingOpen access status: Normalized open-access status: open.
- not scoredPublication license: Not checked or no result supplied; no credibility inference made.
- not scoredPublication version: A publication version was supplied but is not scored.
- cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty.
Cite this work
BibTeX
@article{allodium:10.3389/fncom.2021.799977,
title = {cuSCNN: A Secure and Batch-Processing Framework for Privacy-Preserving Convolutional Neural Network Prediction on GPU.},
author = {Bai Y and Liu Q and Wu W and Feng Y},
year = {2021},
journal = {Frontiers in computational neuroscience},
doi = {10.3389/fncom.2021.799977},
url = {https://doi.org/10.3389/fncom.2021.799977}
}RIS
TY - JOUR TI - cuSCNN: A Secure and Batch-Processing Framework for Privacy-Preserving Convolutional Neural Network Prediction on GPU. AU - Bai Y AU - Liu Q AU - Wu W AU - Feng Y PY - 2021 JO - Frontiers in computational neuroscience DO - 10.3389/fncom.2021.799977 UR - https://doi.org/10.3389/fncom.2021.799977 ER -
APA
Y, B., Q, L., W, W., & Y, F. (2021). cuSCNN: A Secure and Batch-Processing Framework for Privacy-Preserving Convolutional Neural Network Prediction on GPU.. Frontiers in computational neuroscience. https://doi.org/10.3389/fncom.2021.799977
Source records
- pubmed · retrieved 2026-09-25T19:05:38.379Z