Paper Citation Record · LEDGER

SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection against Adversarial Attacks

As of 9 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2507.13170.

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

pith.paper-citation-record.v1
2507.13170 v1

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:34:45.634686Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

42 of 42 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8c785b14-96cf-47d9-8479-88730acbe1d9 · outbound

This paper cites Audio inpainting with gen- erative adversarial network.

SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection against Adversarial Attacks Audio inpainting with gen- erative adversarial network

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:34:50.985220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a205bc3b-f9e8-454d-8e1f-96b4ed541dc5 · outbound

This paper cites Securing Social Media Against Deepfakes using Identity, Behavioral, and Geometric Signatures.

SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection against Adversarial Attacks Securing Social Media Against Deepfakes using Identity, Behavioral, and Geometric Signatures

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-08-06T16:34:46.388048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f461e510-5dd2-4002-9e58-6f0dc8f5b0ba · outbound

This paper cites A Lightweight and Interpretable Deepfakes Detection Framework.

SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection against Adversarial Attacks A Lightweight and Interpretable Deepfakes Detection Framework

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-08-06T16:34:46.242901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 60dd0e24-d32b-444d-a2bb-7b6f72e28b5c · outbound

This paper cites What Does an Audio Deepfake Detector Focus on? A Study in the Time Domain.

SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection against Adversarial Attacks What Does an Audio Deepfake Detector Focus on? A Study in the Time Domain

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-08-06T16:34:46.134157Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2955585c-2443-4998-848b-a8127ef81363 · outbound

This paper cites Deep metric learning using triplet network.

SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection against Adversarial Attacks Deep metric learning using triplet network

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:34:50.973667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9f1d71e5-f71e-48eb-ac23-14059247d741 · outbound

This paper cites Holmes: health online model ensemble serving for deep learning models in intensive care units.

SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection against Adversarial Attacks Holmes: health online model ensemble serving for deep learning models in intensive care units

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:34:50.962619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b7463af2-e22d-4282-8ec8-1549130cf476 · outbound

This paper cites To- wards end-to-end synthetic speech detection.

SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection against Adversarial Attacks To- wards end-to-end synthetic speech detection

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:34:50.951786Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c6f995c3-fcfe-4228-952a-37c7681ed933 · outbound

This paper cites Ibm unveils ai model to detect deepfakes in media,.

SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection against Adversarial Attacks Ibm unveils ai model to detect deepfakes in media,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:34:50.940944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ec1710b6-7c59-4a8d-8ddc-f32b36a2836c · outbound

This paper cites Blind Restoration of Real-World Audio by 1D Operational GANs.

SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection against Adversarial Attacks Blind Restoration of Real-World Audio by 1D Operational GANs

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-08-06T16:34:45.973979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3f529c65-2125-4edb-ad4c-8a862bc7c49d · outbound

This paper cites Pushing the limits of raw waveform speaker recognition.

SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection against Adversarial Attacks Pushing the limits of raw waveform speaker recognition

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:34:50.727700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 84a0bff1-ffc2-47d5-87be-f68ee2476e09 · outbound

This paper cites Defense against adversarial attacks on audio deepfake detection.Interspeech,.

SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection against Adversarial Attacks Defense against adversarial attacks on audio deepfake detection.Interspeech,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:34:50.493192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 36ddc314-4690-425a-a779-9dc93896d302 · outbound

This paper cites Bridging the spoof gap: A unified parallel aggregation network for voice presen- tation attacks, 2023.

SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection against Adversarial Attacks Bridging the spoof gap: A unified parallel aggregation network for voice presen- tation attacks, 2023

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:34:50.258736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 678c223b-3e9a-412f-bdf2-a229107de811 · outbound

This paper cites Securing voice biometrics: One-shot learning approach for audio deepfake detection.

SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection against Adversarial Attacks Securing voice biometrics: One-shot learning approach for audio deepfake detection

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:34:49.969802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 085d9dcd-ad33-4cf8-9053-a96fd27e1369 · outbound

This paper cites Spotnet: A spoofing-aware transformer network for effective synthetic speech detection.

SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection against Adversarial Attacks Spotnet: A spoofing-aware transformer network for effective synthetic speech detection

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:34:49.797496Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c09a625b-0642-4d66-8462-991852715472 · outbound

This paper cites Battling voice spoofing: a review, com- parative analysis, and generalizability evaluation of state-of- the-art voice spoofing counter measures.

SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection against Adversarial Attacks Battling voice spoofing: a review, com- parative analysis, and generalizability evaluation of state-of- the-art voice spoofing counter measures

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:34:49.679645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 54a7519b-1d89-4795-8814-62015af4e9f9 · outbound

This paper cites Frame-to-utterance convergence: A spectra-temporal ap- proach for unified spoofing detection.

SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection against Adversarial Attacks Frame-to-utterance convergence: A spectra-temporal ap- proach for unified spoofing detection

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:34:49.540926Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 97c0058c-2747-42d4-aa4d-1432e68f2019 · outbound

This paper cites Ro- bust deepfake audio detection via bi-level optimization.

SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection against Adversarial Attacks Ro- bust deepfake audio detection via bi-level optimization

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:34:49.417732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation de8ed691-12fe-42e0-aed8-232873be0ae2 · outbound

This paper cites Safeear: Content privacy-preserving audio deepfake detection.

SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection against Adversarial Attacks Safeear: Content privacy-preserving audio deepfake detection

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:34:49.281527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5fb06852-5315-4f00-a41c-da4bafa068d5 · outbound

This paper cites De- tecting deepfake voice using explainable deep learning tech- niques.

SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection against Adversarial Attacks De- tecting deepfake voice using explainable deep learning tech- niques

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:34:49.142451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation dd0c5973-fb54-4310-bd3c-0ab71e7518c4 · outbound

This paper cites Does audio deep- fake detection generalize? Interspeech, 2022.

SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection against Adversarial Attacks Does audio deep- fake detection generalize? Interspeech, 2022

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:34:48.987666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 46c11c80-7b5f-4a74-9f6f-15a3f1d64a16 · outbound

This paper cites Segan: Speech enhancement generative adversarial network.

SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection against Adversarial Attacks Segan: Speech enhancement generative adversarial network

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:34:48.891313Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7e28d2d5-dd5e-421d-864d-bb0a6a7c3d9c · outbound

This paper cites Audio-deepfake detection: Adversarial attacks and counter- measures.

SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection against Adversarial Attacks Audio-deepfake detection: Adversarial attacks and counter- measures

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:34:48.814114Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d4112070-b8e9-46fb-8e27-f1e642d767e9 · outbound

This paper cites Defending against voice-based deepfake fraud attacks, 2024.

SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection against Adversarial Attacks Defending against voice-based deepfake fraud attacks, 2024

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:34:48.695650Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f65989e3-f0db-4d86-bc01-31b92f806410 · outbound

This paper cites End-to-end anti-spoofing with rawnet2.

SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection against Adversarial Attacks End-to-end anti-spoofing with rawnet2

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:34:48.581575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 4e3ba99c-29f1-4641-9efa-08707c45f091 · outbound

This paper cites Rawboost: A raw data boost- ing and augmentation method applied to automatic speaker verification anti-spoofing.

SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection against Adversarial Attacks Rawboost: A raw data boost- ing and augmentation method applied to automatic speaker verification anti-spoofing

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:34:48.375869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c66fac7e-7673-480d-b370-ef0d6426958a · outbound

This paper cites ASVspoof 2019: Future Horizons in Spoofed and Fake Audio Detection.

SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection against Adversarial Attacks ASVspoof 2019: Future Horizons in Spoofed and Fake Audio Detection

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T16:34:44.610455Z

Source-reported events for the cited work

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Observation ea7542a0-d49c-49a6-9749-58a08a9d4290 · outbound

This paper cites Enhanced adversarial attack for avoidance of fake image detection.

SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection against Adversarial Attacks Enhanced adversarial attack for avoidance of fake image detection

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:34:48.232172Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 56f86c87-5133-41cb-a671-4b62973bdc89 · outbound

This paper cites Anti- forensic against double jpeg compression detection using adversarial generative network.

SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection against Adversarial Attacks Anti- forensic against double jpeg compression detection using adversarial generative network

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:34:48.079997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7ac271a2-4173-4178-a48d-91b8f5e4c609 · outbound

This paper cites Analysis of generative adversarial network targeting anti-forensic in jpeg compressed domain.

SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection against Adversarial Attacks Analysis of generative adversarial network targeting anti-forensic in jpeg compressed domain

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:34:47.761068Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 93cf67c1-5811-404e-8dae-d591521ec0e3 · outbound

This paper cites A robust open-set multi-instance learning for defending adversarial attacks in digital image.

SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection against Adversarial Attacks A robust open-set multi-instance learning for defending adversarial attacks in digital image

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:34:47.598636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5401da52-25c9-46b6-81f4-0272cc8bb968 · outbound

This paper cites Deep learning-based counter anti-forensic of gan-based attack in hevc compressed domain using coding pattern analysis.

SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection against Adversarial Attacks Deep learning-based counter anti-forensic of gan-based attack in hevc compressed domain using coding pattern analysis

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:34:47.479145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5e58c179-27a8-4a1e-a748-13bc8c532594 · outbound

This paper cites Transferable adversarial attacks on 9 audio deepfake detection.

SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection against Adversarial Attacks Transferable adversarial attacks on 9 audio deepfake detection

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:34:47.320573Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c1651161-35ef-43d3-8740-bfc3098efcd9 · outbound

This paper cites CSI-Net: Unified Human Body Characterization and Pose Recognition.

SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection against Adversarial Attacks CSI-Net: Unified Human Body Characterization and Pose Recognition

Reference 33

Resolution: verified exact; local_arxiv, observed 2026-08-06T16:34:45.806549Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c9e0730f-4bf5-4467-a243-b82e9b36e8b6 · outbound

This paper cites Abc- capsnet: Attention-based cascaded capsule network for au- dio deepfake detection.

SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection against Adversarial Attacks Abc- capsnet: Attention-based cascaded capsule network for au- dio deepfake detection

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:34:47.151666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5487924b-6dc4-459b-9cf3-0067268a6497 · outbound

This paper cites Defense against adversarial attacks on spoofing countermea- sures of asv.

SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection against Adversarial Attacks Defense against adversarial attacks on spoofing countermea- sures of asv

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:34:46.977359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3e93ee80-8a9c-44cc-b366-c89c5911b7a0 · outbound

This paper cites CLAD: Robust Audio Deepfake Detection Against Manipulation Attacks with Contrastive Learning.

SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection against Adversarial Attacks CLAD: Robust Audio Deepfake Detection Against Manipulation Attacks with Contrastive Learning

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-06T16:34:45.355074Z

Source-reported events for the cited work

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Observation 44001664-411b-418a-859a-000eca495add · outbound

This paper cites A robust audio deepfake detection system via multi-view feature.

SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection against Adversarial Attacks A robust audio deepfake detection system via multi-view feature

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:34:46.821770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation bfd97555-55ee-4754-8a84-5beae987e621 · outbound

This paper cites Half-truth: A partially fake audio detection dataset.

SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection against Adversarial Attacks Half-truth: A partially fake audio detection dataset

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:34:46.696231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a7459424-864f-475c-b64b-8077a4d895e9 · outbound

This paper cites Audio deep- fake detection with self-supervised xls-r and sls classifier.

SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection against Adversarial Attacks Audio deep- fake detection with self-supervised xls-r and sls classifier

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:34:46.527157Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 56279fa9-8d4d-4255-84a1-31c2a7138e26 · outbound

This paper cites I Can Hear You: Selective Robust Training for Deepfake Audio Detection.

SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection against Adversarial Attacks I Can Hear You: Selective Robust Training for Deepfake Audio Detection

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-06T16:34:45.634686Z

Source-reported events for the cited work

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Observation 98c87d50-9ce9-4c1c-9057-cdf5cd90b88c · outbound

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SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection against Adversarial Attacks Unresolved cited work

Reference 60

Resolution: unresolved; raw_fallback, observed 2026-08-06T16:34:47.933165Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 991445c2-4b15-48e2-af56-568b5eade8f4 · outbound

This paper cites an unresolved cited work.

SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection against Adversarial Attacks Unresolved cited work

Reference 2024

Resolution: parse uncertain; raw_fallback, observed 2026-08-06T16:34:50.929462Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Pith citing papers

No inbound Pith citation observations are available.