How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference | Paper Citation Record

Observation f1971fc3-eca1-49ac-8d94-be3f223dbdf4 · outbound

This paper cites TinyML Security: Exploring Vulnerabilities in Resource-Constrained Machine Learning Systems.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference TinyML Security: Exploring Vulnerabilities in Resource-Constrained Machine Learning Systems

Reference 1

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Observation 30a520d0-7c2e-4310-8dac-3041ba6d9f58 · outbound

This paper cites Collaborative inference for ai- empowered iot devices,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Collaborative inference for ai- empowered iot devices,

Reference 2

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Observation 58468491-fec1-47b5-87a4-d1d198f06f36 · outbound

This paper cites Collaborative in- ference via ensembles on the edge,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Collaborative in- ference via ensembles on the edge,

Reference 3

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This paper cites Elastic collaborative edge intelligence for uav swarm: Architecture, challenges, and opportunities,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Elastic collaborative edge intelligence for uav swarm: Architecture, challenges, and opportunities,

Reference 4

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This paper cites an unresolved cited work.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Unresolved cited work

Reference 5

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Observation 903da55b-63d6-47da-a0bf-7c40fb1343c4 · outbound

This paper cites Model inversion attacks against collaborative inference,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Model inversion attacks against collaborative inference,

Reference 6

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Observation b261af70-0dcc-4b89-91fd-a6d834fef84d · outbound

This paper cites Measuring data reconstruction defenses in collaborative inference systems,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Measuring data reconstruction defenses in collaborative inference systems,

Reference 7

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Observation 913c3aa5-207b-4912-9868-0ab1333fb3af · outbound

This paper cites Ginver: Generative model inversion attacks against collaborative inference,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Ginver: Generative model inversion attacks against collaborative inference,

Reference 8

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Observation 659327e1-82ea-49c1-aae8-0733fc9755a2 · outbound

This paper cites Member- ship inference attacks and generalization: A causal perspective,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Member- ship inference attacks and generalization: A causal perspective,

Reference 9

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Observation 75aea5a3-74de-4f66-857c-aee2d0efc3fc · outbound

This paper cites Neural network inversion in adversarial setting via background knowledge alignment,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Neural network inversion in adversarial setting via background knowledge alignment,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:48:44.138516Z

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Observation 94d4506d-5f03-4a31-8134-117e14f24b9f · outbound

This paper cites The secret revealer: Generative model- inversion attacks against deep neural networks,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference The secret revealer: Generative model- inversion attacks against deep neural networks,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:48:44.119339Z

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Observation 4843144e-c722-4606-9c53-d86eb4055969 · outbound

This paper cites Unstoppable attack: Label-only model inversion via conditional diffusion model,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Unstoppable attack: Label-only model inversion via conditional diffusion model,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:48:44.100454Z

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Observation a510f3ba-7856-4c00-8b97-e20083e74110 · outbound

This paper cites Privacy in pharmacogenetics: An {End-to-End} case study of personalized warfarin dosing,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Privacy in pharmacogenetics: An {End-to-End} case study of personalized warfarin dosing,

Reference 13

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Observation b95c6370-3748-4415-91a7-1fafdb535050 · outbound

This paper cites Are your sensitive at- tributes private? novel model inversion attribute inference attacks on classification models,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Are your sensitive at- tributes private? novel model inversion attribute inference attacks on classification models,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:48:44.063247Z

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Observation eee8171c-3da7-41f9-80d4-b046adad16f4 · outbound

This paper cites Privacy-preserving autoencoder for col- laborative object detection,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Privacy-preserving autoencoder for col- laborative object detection,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:48:44.042706Z

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Observation 38ec479a-2aa0-4559-b169-aed82dd08ed2 · outbound

This paper cites Attacking and protecting data privacy in edge–cloud collaborative inference systems,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Attacking and protecting data privacy in edge–cloud collaborative inference systems,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:48:44.023402Z

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Observation 965128de-ca1f-4c6a-8712-1fef13f3065e · outbound

This paper cites Privacy-preserving Security Inference Towards Cloud-Edge Collaborative Using Differential Privacy.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Privacy-preserving Security Inference Towards Cloud-Edge Collaborative Using Differential Privacy

Reference 17

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Observation 26abc8e5-a1e2-44da-80f9-fcb877c5cd1c · outbound

This paper cites Bilateral dependency optimization: Defending against model-inversion attacks,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Bilateral dependency optimization: Defending against model-inversion attacks,

Reference 18

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Observation 994aa6d1-0407-4e4a-b8e7-75bf4b816892 · outbound

This paper cites Privacy-preserving task-oriented semantic communications against model inversion attacks,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Privacy-preserving task-oriented semantic communications against model inversion attacks,

Reference 19

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Observation 78026bce-1836-47fa-8bca-22d9e4b4a4ad · outbound

This paper cites Patrol: Privacy-oriented pruning for collaborative inference against model inversion attacks,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Patrol: Privacy-oriented pruning for collaborative inference against model inversion attacks,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:48:43.963620Z

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Observation 1e6302a6-b151-465d-890e-bb449110e985 · outbound

This paper cites Improving robustness to model inver- sion attacks via mutual information regularization,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Improving robustness to model inver- sion attacks via mutual information regularization,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:48:43.944471Z

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Observation fa239f33-c0e3-4909-84fa-501e5a5f04fe · outbound

This paper cites Not all features are equal: Discovering essential features for preserving prediction privacy,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Not all features are equal: Discovering essential features for preserving prediction privacy,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:48:43.922760Z

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Observation eb62aae9-004e-49b8-9a4f-906d8738d918 · outbound

This paper cites Side-channel attacks based on multi-loss regularized denoising autoencoder,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Side-channel attacks based on multi-loss regularized denoising autoencoder,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:48:43.905951Z

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Observation 254f7bff-595e-4454-a6a5-1a825e4b812e · outbound

This paper cites Mutual information neural estimation,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Mutual information neural estimation,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:48:43.886233Z

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Observation a20582c8-7d3c-487f-8c79-2f01e536bbf6 · outbound

This paper cites Squeeze-and-excitation networks,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Squeeze-and-excitation networks,

Reference 25

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This paper cites Rotate to attend: Convolutional triplet attention module,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Rotate to attend: Convolutional triplet attention module,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:48:43.857209Z

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Observation c69a58f0-0940-4e39-ac20-d4e6b98d0040 · outbound

This paper cites Cbam: Convolutional block attention module,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Cbam: Convolutional block attention module,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:48:43.838530Z

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Observation fb2385bc-b1f2-4eb1-a003-1c1eb0af8ca3 · outbound

This paper cites Passive Inference Attacks on Split Learning via Adversarial Regularization.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Passive Inference Attacks on Split Learning via Adversarial Regularization

Reference 28

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Observation a720b835-6c23-4aff-9280-fbe7d0e63a9e · outbound

This paper cites Model inversion attacks that exploit confidence information and basic countermeasures,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Model inversion attacks that exploit confidence information and basic countermeasures,

Reference 29

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Observation 46f302fb-90e3-45a7-8eaa-3d015f35a9cf · outbound

This paper cites Nonlinear total variation based noise removal algorithms,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Nonlinear total variation based noise removal algorithms,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:48:43.808640Z

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Observation 74b13eaa-a361-474c-ae75-ef18b549f4cb · outbound

This paper cites Analysis and utilization of hidden information in model inversion attacks,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Analysis and utilization of hidden information in model inversion attacks,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:48:43.791360Z

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Observation dd18e0c9-1095-42c4-bb43-91b5e788c831 · outbound

This paper cites Medical image denoising using convolutional denoising autoencoders,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Medical image denoising using convolutional denoising autoencoders,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:48:43.774213Z

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Observation 0e62e35e-f764-4efe-96e0-8aa6638498f1 · outbound

This paper cites Be Careful What You Smooth For: Label Smoothing Can Be a Privacy Shield but Also a Catalyst for Model Inversion Attacks.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Be Careful What You Smooth For: Label Smoothing Can Be a Privacy Shield but Also a Catalyst for Model Inversion Attacks

Reference 33

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Observation 9890e370-2164-4071-b56a-48bef73f24cc · outbound

This paper cites PrivaScissors: Enhance the Privacy of Collaborative Inference through the Lens of Mutual Information.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference PrivaScissors: Enhance the Privacy of Collaborative Inference through the Lens of Mutual Information

Reference 34

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Observation ad8949e0-9dbc-4046-836a-94758671f882 · outbound

This paper cites Club: A contrastive log-ratio upper bound of mutual information,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Club: A contrastive log-ratio upper bound of mutual information,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:48:43.757934Z

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Observation ac096976-bfb2-44f7-ac3a-1ea2984975c5 · outbound

This paper cites The Limitations of Adversarial Training and the Blind-Spot Attack.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference The Limitations of Adversarial Training and the Blind-Spot Attack

Reference 36

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Observation 3a71759c-ba4f-4423-a6e1-0f28c48284d3 · outbound

This paper cites {FaceObfuscator}: Defending deep learning-based privacy attacks with gradient descent-resistant features in face recognition,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference {FaceObfuscator}: Defending deep learning-based privacy attacks with gradient descent-resistant features in face recognition,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:48:43.740822Z

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Observation 61a88d00-b33e-4310-a4e6-2cdce93cacaa · outbound

This paper cites Deep residual learning for image recognition,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Deep residual learning for image recognition,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:48:43.723629Z

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Observation 3d331df8-5dd7-4b03-9826-1e0d338c3a7a · outbound

This paper cites Sok: Model inversion attack landscape: Taxonomy, chal- lenges, and future roadmap,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Sok: Model inversion attack landscape: Taxonomy, chal- lenges, and future roadmap,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:48:43.706184Z

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Observation c9ff0232-fa8a-43a3-a365-899dc1523236 · outbound

This paper cites Text Revealer: Private Text Reconstruction via Model Inversion Attacks against Transformers.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Text Revealer: Private Text Reconstruction via Model Inversion Attacks against Transformers

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-10T22:48:43.009486Z

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Observation 5511382f-56af-410a-be02-2dc2b893dfe5 · outbound

This paper cites Pseudo label-guided model in- version attack via conditional generative adversarial network,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Pseudo label-guided model in- version attack via conditional generative adversarial network,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:48:43.689270Z

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Observation 1f6a6fb5-cae1-4fd4-98ee-39a6d4406482 · outbound

This paper cites Query-efficient model inversion attacks: An information flow view,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Query-efficient model inversion attacks: An information flow view,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:48:43.671775Z

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Observation 2e924db0-e957-4031-9759-27f0c8454643 · outbound

This paper cites Classificatory notes on the production and transmis- sion of technological knowledge,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Classificatory notes on the production and transmis- sion of technological knowledge,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:48:43.656009Z

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Observation ba80a915-b38a-41a6-9259-800316cab1bc · outbound

This paper cites On the vulnerability of skip connections to model inversion attacks,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference On the vulnerability of skip connections to model inversion attacks,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:48:43.640670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8041be33-66fe-4d16-9d11-241b285da920 · outbound

This paper cites Asymptotic evaluation of certain markov process expectations for large time. iv,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Asymptotic evaluation of certain markov process expectations for large time. iv,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:48:43.622349Z

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Observation 2fbd4625-ee99-4e81-a367-20f807a0942c · outbound

This paper cites Learning multiple layers of features from tiny images,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Learning multiple layers of features from tiny images,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:48:43.604513Z

Source-reported events for the cited work

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Observation dafe771b-e54e-48e5-b14f-2a4c0db06f16 · outbound

This paper cites Feature screening via distance corre- lation learning,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Feature screening via distance corre- lation learning,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:48:43.586759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ff4606d0-3e29-4c66-8291-baff5bb242f1 · outbound

This paper cites Pearson correlation coefficient,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Pearson correlation coefficient,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:48:43.570836Z

Source-reported events for the cited work

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Observation e304cb8e-1aa5-491b-b05a-b636d2f44b4f · outbound

This paper cites Model inversion robust- ness: Can transfer learning help?.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Model inversion robust- ness: Can transfer learning help?

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:48:43.553760Z

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Observation 86929a9b-751f-4a2d-b8c5-fe54ff888e39 · outbound

This paper cites Fisher information and stochastic complexity,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Fisher information and stochastic complexity,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:48:43.535484Z

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Observation de73955f-1733-4cab-8e4b-1a4a3562fb6d · outbound

This paper cites Inception-v4, inception- resnet and the impact of residual connections on learning,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Inception-v4, inception- resnet and the impact of residual connections on learning,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:48:43.517038Z

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Observation 4796522d-044a-4d4d-bb07-3106da1d7656 · outbound

This paper cites Kernel methods for measuring indepen- dence,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Kernel methods for measuring indepen- dence,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:48:43.499253Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c0ac6a5c-e63c-4313-86a0-3f30eaa5f534 · outbound

This paper cites Plug & play attacks: Towards robust and flexible model inversion attacks,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Plug & play attacks: Towards robust and flexible model inversion attacks,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:48:43.481028Z

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Observation 531b0c36-d0fc-4ff2-9c97-ff1fc20ea26d · outbound

This paper cites Measuring statistical de- pendence with hilbert-schmidt norms,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Measuring statistical de- pendence with hilbert-schmidt norms,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:48:43.458404Z

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Observation 82a37c23-598d-47d4-924d-02baf5ec1b5c · outbound

This paper cites A data-driven approach to cleaning large face datasets,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference A data-driven approach to cleaning large face datasets,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:48:43.439216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7c833ea4-0f4d-4f62-a86c-f7743ac8cff4 · outbound

This paper cites Deep learning face attributes in the wild,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Deep learning face attributes in the wild,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:48:43.419561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f252451f-d8a1-4962-88f8-b14d4b0aca06 · outbound

This paper cites Curated dataset for covid-19 posterior-anterior chest radiography images (x-rays),.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Curated dataset for covid-19 posterior-anterior chest radiography images (x-rays),

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:48:43.400086Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4f9a31b1-d468-4ae9-845e-4ce8aa1e816b · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-10T22:48:43.173915Z

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Observation 1ac3b6b1-4b42-4c65-9d6f-42593a3a6f2d · outbound

This paper cites Deep learning with differential privacy,.

How Breakable Is Privacy: Probing and Resisting Model Inversion Attacks in Collaborative Inference Deep learning with differential privacy,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:48:43.377830Z

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