The DOI matches its Crossref record; 38 of the 38 references it cites were found in a registry or an index.
Privacy-preserving outsourced classification in cloud computing
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Speech recognition with deep recurrent neural networks
Graves, A., Mohamed, A.-R., & Hinton, G. (2013) · 2013 IEEE International Conference on Acoustics, Speech and Signal Processing · doi:10.1109/icassp.2013.6638947 · Cited by 8,893
Fully homomorphic encryption using ideal lattices
Gentry, C. (2009) · Proceedings of the forty-first annual ACM symposium on Theory of computing · doi:10.1145/1536414.1536440 · Cited by 6,806
How to generate and exchange secrets
Yao, A. C.-C. (1986) · 27th Annual Symposium on Foundations of Computer Science (sfcs 1986) · doi:10.1109/sfcs.1986.25 · Cited by 3,733
Privacy-preserving data mining
Agrawal, R., & Srikant, R. (2000) · ACM SIGMOD Record · doi:10.1145/335191.335438 · Cited by 2,961
Goldwasser, S., & Micali, S. (1984) · Journal of Computer and System Sciences · doi:10.1016/0022-0000(84)90070-9 · Cited by 2,603
Privacy-preserving deep learning
Shokri, R., & Shmatikov, V. (2015) · Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security · doi:10.1145/2810103.2813687 · Cited by 2,356
Fully Homomorphic Encryption over the Integers
van Dijk, M., Gentry, C., Halevi, S., & Vaikuntanathan, V. (2010) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-13190-5_2 · Cited by 1,858
Evaluating 2-DNF Formulas on Ciphertexts
Boneh, D., Goh, E.-J., & Nissim, K. (2005) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-30576-7_18 · Cited by 1,692
(Leveled) Fully Homomorphic Encryption without Bootstrapping
Brakerski, Z., Gentry, C., & Vaikuntanathan, V. (2014) · ACM Transactions on Computation Theory · doi:10.1145/2633600 · Cited by 1,430
A Secure and Dynamic Multi-Keyword Ranked Search Scheme over Encrypted Cloud Data
Xia, Z., Wang, X., Sun, X., & Wang, Q. (2016) · IEEE Transactions on Parallel and Distributed Systems · doi:10.1109/tpds.2015.2401003 · Cited by 1,181
Cited by
DeepChain: Auditable and Privacy-Preserving Deep Learning with Blockchain-based Incentive
Weng, J., Weng, J., Zhang, J., Li, M., Zhang, Y., & Luo, W. (2019) · IEEE Transactions on Dependable and Secure Computing · doi:10.1109/tdsc.2019.2952332 · Cited by 610
Significant Permission Identification for Machine-Learning-Based Android Malware Detection
Li, J., Sun, L., Yan, Q., Li, Z., Srisa-an, W., & Ye, H. (2018) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2017.2789219 · Cited by 607
Self-citationA hybrid particle swarm optimization algorithm using adaptive learning strategy
Wang, F., Zhang, H., Li, K., Lin, Z., Yang, J., & Shen, X.-L. (2018) · Information Sciences · doi:10.1016/j.ins.2018.01.027 · Cited by 284
Wang, W., Zhao, M., & Wang, J. (2019) · Journal of Ambient Intelligence and Humanized Computing · doi:10.1007/s12652-018-0803-6 · Cited by 284
An ID-Based Linearly Homomorphic Signature Scheme and Its Application in Blockchain
Lin, Q., Yan, H., Huang, Z., Chen, W., Shen, J., & Tang, Y. (2018) · IEEE Access · doi:10.1109/access.2018.2809426 · Cited by 202
Self-citation
Metadata
- Authors
- Li, P., Li, J., Huang, Z., Gao, C.-Z., Chen, W.-B., & Chen, K.
- Venue
- Cluster Computing
- Published
- 2017-04-08
- Volume
- 21
- Issue
- 1
- Pages
- 277-286
- ISSN
- 1386-7857 (ISSN-L)
- 1573-7543
- OpenAlex
- W2604462068
- Cited by
- 309
- References
- 38
- FWCI
- 93.73
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Privacy-preserving outsourced classification in cloud computing. https://app.cochat.ai/papers/10.1007/s10586-017-0849-9
- The paper
- Li, P., Li, J., Huang, Z., Gao, C.-Z., Chen, W.-B., & Chen, K. (2018). Privacy-preserving outsourced classification in cloud computing. Cluster Computing. https://doi.org/10.1007/s10586-017-0849-9
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.