Paper Citation Record · LEDGER

Privacy Leakage on DNNs: A Survey of Model Inversion Attacks and Defenses

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2402.04013.

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

pith.paper-citation-record.v1
2402.04013 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T15:18:14.149178Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T19:40:06.648411Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 11441e65-ed70-45e5-b3f8-9ff5ff52bdf5 · inbound

Top Ten Challenges Towards Agentic Neural Graph Databases cites this paper.

Top Ten Challenges Towards Agentic Neural Graph Databases Privacy Leakage on DNNs: A Survey of Model Inversion Attacks and Defenses

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-10T15:18:14.149178Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 39368c2e-e445-483e-a1d9-327ba021473c · inbound

Deep Learning Model Inversion Attacks and Defenses: A Comprehensive Survey cites this paper.

Deep Learning Model Inversion Attacks and Defenses: A Comprehensive Survey Privacy Leakage on DNNs: A Survey of Model Inversion Attacks and Defenses

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-09T21:58:40.418983Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7ff988e6-375b-4372-bc3a-9df58df37688 · inbound

Hey, That's My Data! Token-Only Dataset Inference in Large Language Models cites this paper.

Hey, That's My Data! Token-Only Dataset Inference in Large Language Models Privacy Leakage on DNNs: A Survey of Model Inversion Attacks and Defenses

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-19T11:07:15.810834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c1178347-abde-41a3-8194-8cdb9a697f4d · inbound

Theoretically Unmasking Inference Attacks Against LDP-Protected Clients in Federated Vision Models cites this paper.

Theoretically Unmasking Inference Attacks Against LDP-Protected Clients in Federated Vision Models Privacy Leakage on DNNs: A Survey of Model Inversion Attacks and Defenses

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T00:32:42.237738Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 33aadbd3-29e2-4eab-9f90-b5a331e02b91 · inbound

Intellectual Property in Graph-Based Machine Learning as a Service: Attacks and Defenses cites this paper.

Intellectual Property in Graph-Based Machine Learning as a Service: Attacks and Defenses Privacy Leakage on DNNs: A Survey of Model Inversion Attacks and Defenses

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-05T15:39:55.367619Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f68baac1-2a12-4241-8c0a-78b94cdb2bd3 · inbound

Revisiting the Privacy Risks of Split Inference: A GAN-Based Data Reconstruction Attack via Progressive Feature Optimization cites this paper.

Revisiting the Privacy Risks of Split Inference: A GAN-Based Data Reconstruction Attack via Progressive Feature Optimization Privacy Leakage on DNNs: A Survey of Model Inversion Attacks and Defenses

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-05T15:01:34.520244Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff7da556-1f73-4eb5-9d8a-c7b7c4bead23 · inbound

Safety, Security, and Cognitive Risks in World Models cites this paper.

Safety, Security, and Cognitive Risks in World Models Privacy Leakage on DNNs: A Survey of Model Inversion Attacks and Defenses

Reference 65

Resolution: verified exact; arxiv_id, observed 2026-05-13T22:38:22.234812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f1dc313a-dca2-4eb9-a1fa-02907cd3c3b8 · inbound

Before the Mic: Physical-Layer Voiceprint Anonymization with Acoustic Metamaterials cites this paper.

Before the Mic: Physical-Layer Voiceprint Anonymization with Acoustic Metamaterials Privacy Leakage on DNNs: A Survey of Model Inversion Attacks and Defenses

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-05-11T14:01:04.680952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 862ed18c-c35a-4523-b48e-3adbedea3d90 · inbound

Bypassing Copyright Protection in Diffusion-based Customization via Two-Stage Latent Feature Optimization cites this paper.

Bypassing Copyright Protection in Diffusion-based Customization via Two-Stage Latent Feature Optimization Privacy Leakage on DNNs: A Survey of Model Inversion Attacks and Defenses

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-07-02T21:37:25.002940Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7eda2f04-5d04-44a4-b405-a7d9b9af63f6 · inbound

Leaking Circuit Secrets: Gradient Leakage Attacks on Graph Neural Networks cites this paper.

Leaking Circuit Secrets: Gradient Leakage Attacks on Graph Neural Networks Privacy Leakage on DNNs: A Survey of Model Inversion Attacks and Defenses

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-07-04T19:40:06.667431Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.