Paper Citation Record · LEDGER

A Novel Privacy-Preserving Deep Learning Scheme without Using Cryptography Component

As of 15 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 1 inbound Pith citation observation for arXiv:1908.07701.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
1908.07701 v2

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T12:12:33.528875Z

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T12:12:33.515885Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-14T12:12:33.644788Z

Reference resolution

29 of 29 outbound references displayed

verified exact11
verified fuzzy12
unresolved6
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c781e450-b900-4c42-9361-ee17ec8baf5e · outbound

This paper cites Machine learning in vlsi computer -aided design URL: https://www.springer.com/us/book/9783030046651, doi:10.1007/978-3-030-04666-8.

A Novel Privacy-Preserving Deep Learning Scheme without Using Cryptography Component Machine learning in vlsi computer -aided design URL: https://www.springer.com/us/book/9783030046651, doi:10.1007/978-3-030-04666-8

Reference 1

Resolution: verified exact; raw_fallback, observed 2026-08-14T12:12:34.508491Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 0cc9bd21-e38f-4828-aff7-9da8c8fec405 · outbound

This paper cites A logic of authentication.

A Novel Privacy-Preserving Deep Learning Scheme without Using Cryptography Component A logic of authentication

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:12:34.690022Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 13cd6a20-ca62-4b93-a0e4-a056dcdd84d4 · outbound

This paper cites QUOTIENT: Two-Party Secure Neural Network Training and Prediction.

A Novel Privacy-Preserving Deep Learning Scheme without Using Cryptography Component QUOTIENT: Two-Party Secure Neural Network Training and Prediction

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-08-14T12:12:34.396256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1764d493-3811-4d88-b2e6-5ba2672be4ce · outbound

This paper cites Cryptology ePrint Archive,Report 2019/338.

A Novel Privacy-Preserving Deep Learning Scheme without Using Cryptography Component Cryptology ePrint Archive,Report 2019/338

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:12:34.677172Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 335d9d4e-d227-4c85-856b-9976eb37a344 · outbound

This paper cites A privacy -preserving protocol for neural-network-based computation, in: Proceedings of the8th Workshop on Multimedia and Security, ACM, New York, NY,USA.

A Novel Privacy-Preserving Deep Learning Scheme without Using Cryptography Component A privacy -preserving protocol for neural-network-based computation, in: Proceedings of the8th Workshop on Multimedia and Security, ACM, New York, NY,USA

Reference 5

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-14T12:12:34.376911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5a5b1c61-42e0-4f1c-a068-e5abd1dbcf14 · outbound

This paper cites an unresolved cited work.

A Novel Privacy-Preserving Deep Learning Scheme without Using Cryptography Component Unresolved cited work

Reference 6

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-14T12:12:34.194249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d8ebafbb-900f-4558-87d7-0282df7d1347 · outbound

This paper cites Numerical Analysis.

A Novel Privacy-Preserving Deep Learning Scheme without Using Cryptography Component Numerical Analysis

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:12:34.663406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5ee5c66e-0d75-4734-b429-071c0d305e28 · outbound

This paper cites Privacy-preserving classification on deep neural network.

A Novel Privacy-Preserving Deep Learning Scheme without Using Cryptography Component Privacy-preserving classification on deep neural network

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:12:34.649193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c6a49bcd-7041-4852-8db4-edbf0dd9f053 · outbound

This paper cites Automatic detection of invasive ductal carcinoma in whole slide images with convolutional neural networks.

A Novel Privacy-Preserving Deep Learning Scheme without Using Cryptography Component Automatic detection of invasive ductal carcinoma in whole slide images with convolutional neural networks

Reference 9

Resolution: verified exact; doi, observed 2026-08-14T12:12:33.609809Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation fbf74457-7b92-4dff-bd4d-a745553cde4c · outbound

This paper cites an unresolved cited work.

A Novel Privacy-Preserving Deep Learning Scheme without Using Cryptography Component Unresolved cited work

Reference 10

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-14T12:12:34.019832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f4ef3f9e-0ddf-4e92-b91e-2f8312569f3e · outbound

This paper cites A Fully Homomorphic Encryption Scheme.

A Novel Privacy-Preserving Deep Learning Scheme without Using Cryptography Component A Fully Homomorphic Encryption Scheme

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:12:34.635183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5a8d97e8-71e0-41c3-8afe-b93aa2def9dc · outbound

This paper cites an unresolved cited work.

A Novel Privacy-Preserving Deep Learning Scheme without Using Cryptography Component Unresolved cited work

Reference 12

Resolution: unresolved; raw_fallback, observed 2026-08-14T12:12:34.621508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f86f4d08-ef85-4906-82ed-df739c41dbd9 · outbound

This paper cites Cell 172, 1122–1131.

A Novel Privacy-Preserving Deep Learning Scheme without Using Cryptography Component Cell 172, 1122–1131

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:12:34.607396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c9e531dd-f1b5-410f-ac89-5482c1f0b988 · outbound

This paper cites MNIST handwritten digit database URL: http://yann.lecun.com/exdb/mnist/.

A Novel Privacy-Preserving Deep Learning Scheme without Using Cryptography Component MNIST handwritten digit database URL: http://yann.lecun.com/exdb/mnist/

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:12:34.593705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5cd8a1e7-6c10-4c91-a182-6dbb1b66ade3 · outbound

This paper cites Oblivious neural network predictions via minionn transformations, in: Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security, ACM, New York, NY, USA.

A Novel Privacy-Preserving Deep Learning Scheme without Using Cryptography Component Oblivious neural network predictions via minionn transformations, in: Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security, ACM, New York, NY, USA

Reference 15

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-14T12:12:33.862163Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 56950d66-a68d-422a-80d4-04eeb1bcde38 · outbound

This paper cites Understanding deep image representations by inverting them, in: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

A Novel Privacy-Preserving Deep Learning Scheme without Using Cryptography Component Understanding deep image representations by inverting them, in: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:12:34.580310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation af1a09e9-8b18-4bc1-b2a9-f3c984e03061 · outbound

This paper cites Aby 3: A mixed protocol framework for machine learning, pp.

A Novel Privacy-Preserving Deep Learning Scheme without Using Cryptography Component Aby 3: A mixed protocol framework for machine learning, pp

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-14T12:12:33.477707Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f74084aa-f975-4607-a35a-0911ccb55f49 · outbound

This paper cites Secureml: A system for s calable privacy-preserving machine learning, in: 2017 IEEE Symposium on Security and Privacy (SP), pp.

A Novel Privacy-Preserving Deep Learning Scheme without Using Cryptography Component Secureml: A system for s calable privacy-preserving machine learning, in: 2017 IEEE Symposium on Security and Privacy (SP), pp

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:12:34.565657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d21c4176-d1b1-4ca9-b592-67c406ae4c7a · outbound

This paper cites Computationally secure oblivious transfer.

A Novel Privacy-Preserving Deep Learning Scheme without Using Cryptography Component Computationally secure oblivious transfer

Reference 19

Resolution: verified exact; doi, observed 2026-08-14T12:12:33.587048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e894470e-a5b2-46db-af21-a8f25083a7cf · outbound

This paper cites Oblivious neural network computing via homomorphic encryption.

A Novel Privacy-Preserving Deep Learning Scheme without Using Cryptography Component Oblivious neural network computing via homomorphic encryption

Reference 20

Resolution: verified exact; doi, observed 2026-08-14T12:12:33.572823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a1696211-27c3-4521-8268-519fa356dae9 · outbound

This paper cites Enhancing privacy in remote data classification, in: Jajodia, S., Samarati,P., Cimato, S.

A Novel Privacy-Preserving Deep Learning Scheme without Using Cryptography Component Enhancing privacy in remote data classification, in: Jajodia, S., Samarati,P., Cimato, S

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:12:34.550280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 56f7e9bb-ca2e-4a1a-ac5d-76b5a7231792 · outbound

This paper cites DeepSecure: Scalable Provably-Secure Deep Learning.

A Novel Privacy-Preserving Deep Learning Scheme without Using Cryptography Component DeepSecure: Scalable Provably-Secure Deep Learning

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-14T12:12:33.498669Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c3928f7a-7f05-46d9-8007-8031d7b6e20b · outbound

This paper cites Tapas: Tricks to accelerate (encrypted) prediction as a service.

A Novel Privacy-Preserving Deep Learning Scheme without Using Cryptography Component Tapas: Tricks to accelerate (encrypted) prediction as a service

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:12:34.536444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d76816c2-93a3-40a1-a6d0-bd66929cd8b5 · outbound

This paper cites Deep Learning in Neural Networks: An Overview.

A Novel Privacy-Preserving Deep Learning Scheme without Using Cryptography Component Deep Learning in Neural Networks: An Overview

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-14T12:12:33.506989Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f3a5a158-dde7-4c58-9a35-947ac7d9ecdc · outbound

This paper cites Towards Reverse-Engineering Black-Box Neural Networks.

A Novel Privacy-Preserving Deep Learning Scheme without Using Cryptography Component Towards Reverse-Engineering Black-Box Neural Networks

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-14T12:12:33.511344Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dcc08b92-967d-42eb-a514-d62097730668 · outbound

This paper cites A Novel Privacy-Preserving Deep Learning Scheme without Using Cryptography Component.

A Novel Privacy-Preserving Deep Learning Scheme without Using Cryptography Component A Novel Privacy-Preserving Deep Learning Scheme without Using Cryptography Component

Reference 26

Resolution: verified exact; local_arxiv, observed 2026-08-14T12:12:33.649435Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ed027393-c251-45ff-afa9-bfeaa49bd833 · outbound

This paper cites Stealing machine learning models via prediction apis, in: 25th USENIX Security Symposium (USENIX Security 16), USENIX Association, Austin, TX.

A Novel Privacy-Preserving Deep Learning Scheme without Using Cryptography Component Stealing machine learning models via prediction apis, in: 25th USENIX Security Symposium (USENIX Security 16), USENIX Association, Austin, TX

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:12:34.522141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9c6bbe23-5523-434e-8c87-e61aa25e07d9 · outbound

This paper cites Stealing Hyperparameters in Machine Learning.

A Novel Privacy-Preserving Deep Learning Scheme without Using Cryptography Component Stealing Hyperparameters in Machine Learning

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-08-14T12:12:33.629973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8ccc60c5-2454-4ed3-91f9-cf67cf2001f4 · outbound

This paper cites How to generate and exchange secrets, in: 27th Annual Symposium on Foundations of Computer Science (sfcs 1986), pp.

A Novel Privacy-Preserving Deep Learning Scheme without Using Cryptography Component How to generate and exchange secrets, in: 27th Annual Symposium on Foundations of Computer Science (sfcs 1986), pp

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-14T12:12:33.528875Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation dcc08b92-967d-42eb-a514-d62097730668 · inbound