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Paper Citation Record · LEDGER

Stealthy Backdoor Attack to Real-world Models in Android Apps

As of 19 August 2026, this Paper Citation Record lists 58 of 58 outbound references and 1 inbound Pith citation observation for arXiv:2501.01263.

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

pith.paper-citation-record.v1
2501.01263 v1

Coverage vector

measured 58 of 58 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:35:26.132746Z

measured 59 of 59 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-02T11:45:33.273144Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T11:46:54.738438Z

Reference resolution

58 of 58 outbound references displayed

  • verified exact0
  • verified fuzzy37
  • unresolved20
  • parse uncertain1
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 56c044be-e4c4-472f-ab4c-cae7efee86e5 · outbound

This paper cites Multi-modal fusion transformer for end-to-end autonomous driving,.

Stealthy Backdoor Attack to Real-world Models in Android Apps Multi-modal fusion transformer for end-to-end autonomous driving,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:35:27.307661Z

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.

source=pdf_text observed=2026-08-10T22:35:25.791905Z digest=sha256:42fc7d9067de2b0cedf7c1a8f8c385de71c5337e6844d792a87c0def0ac83fc6

Observation 51374fc0-6ddc-497d-9083-4c51bced9a4b · outbound

This paper cites Transformers in medical imaging: A survey,.

Stealthy Backdoor Attack to Real-world Models in Android Apps Transformers in medical imaging: A survey,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:35:27.283639Z

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.

source=pdf_text observed=2026-08-10T22:35:25.799022Z digest=sha256:49228919a8a9813f72c11a21d351214f19b596c110e037328a98ef4660f9fa0b

Observation b638fd74-ae9e-4d37-be83-6eca53f785fe · outbound

This paper cites Killing two birds with one stone: Efficient and robust training of face recognition cnns by partial fc,.

Stealthy Backdoor Attack to Real-world Models in Android Apps Killing two birds with one stone: Efficient and robust training of face recognition cnns by partial fc,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:35:27.263881Z

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.

source=pdf_text observed=2026-08-10T22:35:25.804567Z digest=sha256:bd82f42101f58ded20770faaf49804fe6bd9a5119d5c36e5338bfcdec1c0f88c

Observation 97740b81-4d0e-4a38-a080-ff1ca4f3caa7 · outbound

This paper cites Robustness of on-device models: Adversarial attack to deep learning models on android apps,.

Stealthy Backdoor Attack to Real-world Models in Android Apps Robustness of on-device models: Adversarial attack to deep learning models on android apps,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:35:27.243367Z

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.

source=pdf_text observed=2026-08-10T22:35:25.810228Z digest=sha256:c96e07b525b44d386f863b2b5580117e5e69c2edeb156d169f432dac03a75328

Observation 8f9287c8-920c-445f-ac1f-f956dd887ae8 · outbound

This paper cites Smart app attack: Hacking deep learning models in android apps,.

Stealthy Backdoor Attack to Real-world Models in Android Apps Smart app attack: Hacking deep learning models in android apps,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:35:27.202170Z

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.

source=pdf_text observed=2026-08-10T22:35:25.821947Z digest=sha256:a5848fe19880ae135958d4211f090d266e417815ec0c4f518a6d60d775f335e7

Observation 330667f1-82d0-4f4a-a8ad-72e4b5fd0fae · outbound

This paper cites Adversary for social good: Protecting familial privacy through joint adversarial attacks,.

Stealthy Backdoor Attack to Real-world Models in Android Apps Adversary for social good: Protecting familial privacy through joint adversarial attacks,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:35:27.175312Z

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.

source=pdf_text observed=2026-08-10T22:35:25.828211Z digest=sha256:97099fcb1678493b6637e5ad43c5031c39b784e6433b209d737d954e740d7d83

Observation e01456dd-1e87-40dd-ae46-f423680f6137 · outbound

This paper cites Machine learning on mobile: An on-device inference app for skin cancer detec- tion,.

Stealthy Backdoor Attack to Real-world Models in Android Apps Machine learning on mobile: An on-device inference app for skin cancer detec- tion,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:35:27.157402Z

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.

source=pdf_text observed=2026-08-10T22:35:25.833234Z digest=sha256:53b12fde9e0a828ec6300f0ca8d516e9fe77fca3c03cab1c22c10322c4c7fe90

Observation bb9dd722-c7e4-4c05-b36a-c0f509f6705d · outbound

This paper cites A first look at deep learning apps on smartphones,.

Stealthy Backdoor Attack to Real-world Models in Android Apps A first look at deep learning apps on smartphones,

Reference 8

Resolution
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raw_fallback, observed 2026-08-10T22:35:27.139738Z

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.

source=pdf_text observed=2026-08-10T22:35:25.838592Z digest=sha256:7e833d584d1abf52ff3815b030f2182b0c8f52c551c47477b1520b33bf1b4bb7

Observation da2add1d-9fdc-460b-911e-8869a31cb9d5 · outbound

This paper cites A comprehensive benchmark of deep learning libraries on mobile devices,.

Stealthy Backdoor Attack to Real-world Models in Android Apps A comprehensive benchmark of deep learning libraries on mobile devices,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:35:27.121487Z

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.

source=pdf_text observed=2026-08-10T22:35:25.843547Z digest=sha256:19a8fb4aed16680cebe38ce0239854279d4fbc44b9aa37b70225a777d33fcf3f

Observation 60029fb3-3d1a-4bfb-9c8f-5147d7899ce9 · outbound

This paper cites Tensorflow lite,.

Stealthy Backdoor Attack to Real-world Models in Android Apps Tensorflow lite,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:35:27.104582Z

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.

source=pdf_text observed=2026-08-10T22:35:25.848543Z digest=sha256:acbb7b4a2e22ce57ec75e151c49f25e4f8a51d575c344f106fc57f3e4e697241

Observation 77eeb881-7e45-4297-ab47-57b47d918764 · outbound

This paper cites an unresolved cited work.

Stealthy Backdoor Attack to Real-world Models in Android Apps Unresolved cited work

Reference 11

Resolution
unresolved
raw_fallback, observed 2026-08-10T22:35:27.086462Z

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.

source=pdf_text observed=2026-08-10T22:35:25.853952Z digest=sha256:42253679235feb541796bc68142f57341bef8ae6e1afe74f4232f2eb68c80169

Observation b4d7c25c-f1a6-4604-98e6-f6086c769aa6 · outbound

This paper cites Mind your weight(s): A large- scale study on insufficient machine learning model protection in mobile apps,.

Stealthy Backdoor Attack to Real-world Models in Android Apps Mind your weight(s): A large- scale study on insufficient machine learning model protection in mobile apps,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:35:27.070314Z

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.

source=pdf_text observed=2026-08-10T22:35:25.859190Z digest=sha256:3ded8c08b836405716066454207f19dc985f14ddec8681ecbb98b0d5ba92f7bf

Observation b07b2133-4ced-4b8d-97e1-20fa94fb033e · outbound

This paper cites Under- standing real-world threats to deep learning models in android apps,.

Stealthy Backdoor Attack to Real-world Models in Android Apps Under- standing real-world threats to deep learning models in android apps,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:35:27.052038Z

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.

source=pdf_text observed=2026-08-10T22:35:25.864631Z digest=sha256:b4223caf9aa99566a0d64c3fa2fccab54bfb42f667f7b631147f8f7b9a670ac6

Observation be759d19-eea9-437b-a0af-3b64710ac21c · outbound

This paper cites Backdoor learning: A survey,.

Stealthy Backdoor Attack to Real-world Models in Android Apps Backdoor learning: A survey,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:35:27.033997Z

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.

source=pdf_text observed=2026-08-10T22:35:25.871524Z digest=sha256:424e40b290bbfc0a17211d266a7af3bcab964d914996f8351393b493280e5e70

Observation 3122ec1e-444a-438d-9abf-13c09c8336d5 · outbound

This paper cites Badnl: Backdoor attacks against nlp models with semantic- preserving improvements,.

Stealthy Backdoor Attack to Real-world Models in Android Apps Badnl: Backdoor attacks against nlp models with semantic- preserving improvements,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:35:27.016649Z

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.

source=pdf_text observed=2026-08-10T22:35:25.877278Z digest=sha256:0e55491ab715d32c755d4585473c2f93c407b5190ede99d6e622da9defb4546f

Observation cc83f13d-2031-43b2-9542-e5c9439b91e1 · outbound

This paper cites Deepinspect: A black-box trojan detection and mitigation framework for deep neural networks.

Stealthy Backdoor Attack to Real-world Models in Android Apps Deepinspect: A black-box trojan detection and mitigation framework for deep neural networks

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-10T22:35:25.882489Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:35:25.882489Z digest=sha256:fbe9936b10d9c4901d68d043e22efee240cebcb9c5532675e128c7aed4dfa6ae

Observation 1eeecefb-abcf-4860-82bc-40e3cee95a31 · outbound

This paper cites TABOR: A Highly Accurate Approach to Inspecting and Restoring Trojan Backdoors in AI Systems.

Stealthy Backdoor Attack to Real-world Models in Android Apps TABOR: A Highly Accurate Approach to Inspecting and Restoring Trojan Backdoors in AI Systems

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-10T22:35:25.887391Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:35:25.887391Z digest=sha256:faa19f78fa754dc6d09fbcc245987286cd4205a7eee341c075b2472cc523fe60

Observation 2ed269fe-5573-494e-a001-999770531280 · outbound

This paper cites Composite backdoor attack for deep neural network by mixing existing benign features,.

Stealthy Backdoor Attack to Real-world Models in Android Apps Composite backdoor attack for deep neural network by mixing existing benign features,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:35:26.989346Z

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.

source=pdf_text observed=2026-08-10T22:35:25.897320Z digest=sha256:5345d2cbc9034f7c11242071a1505840c2bc676de203f4b308019b3ee15298ec

Observation e6f79bf4-b022-4c0a-a243-22d9db6d607f · outbound

This paper cites How to backdoor federated learning,.

Stealthy Backdoor Attack to Real-world Models in Android Apps How to backdoor federated learning,

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-10T22:35:25.904234Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:35:25.904234Z digest=sha256:dad340787c5ba45a98fa19ee8631c8f33809c5199c3d663bc2785993c04b7734

Observation 60aca403-7403-48a2-97bd-83308d14a62f · outbound

This paper cites Blind backdoors in deep learning models,.

Stealthy Backdoor Attack to Real-world Models in Android Apps Blind backdoors in deep learning models,

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-10T22:35:25.910184Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:35:25.910184Z digest=sha256:e642c67795e59be575fb1af95df39f8044c36814bf29f1d2e649b09fc3d6f369

Observation db76a302-b428-4893-a394-916b86f948df · outbound

This paper cites Badnets: Evaluating backdooring attacks on deep neural networks,.

Stealthy Backdoor Attack to Real-world Models in Android Apps Badnets: Evaluating backdooring attacks on deep neural networks,

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-10T22:35:25.915451Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:35:25.915451Z digest=sha256:c6a5dc3504cbb5c4749a7a53f14e98232d62921087b3dc79a159d5837fa54959

Observation 6c8f0dc3-c19a-4f83-8526-1c8bd6049a45 · outbound

This paper cites Reflection backdoor: A natural backdoor attack on deep neural networks,.

Stealthy Backdoor Attack to Real-world Models in Android Apps Reflection backdoor: A natural backdoor attack on deep neural networks,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:35:26.941723Z

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.

source=pdf_text observed=2026-08-10T22:35:25.921333Z digest=sha256:cf63ee4c2430d59b734a0d652821067f4cadd798af027b146a1840219b1c92f9

Observation 2e2123ab-6a90-4e6d-a0b5-5ab8968a4235 · outbound

This paper cites Weight poisoning attacks on pretrained models,.

Stealthy Backdoor Attack to Real-world Models in Android Apps Weight poisoning attacks on pretrained models,

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-10T22:35:25.926625Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:35:25.926625Z digest=sha256:80278a53da399c2224ad867d54a4d6829f7617f4752a5681dae180a6650361a3

Observation 836cb4d1-b934-40c2-9c52-05341600c40f · outbound

This paper cites Backdoor attacks against transfer learning with pre-trained deep learn- ing models,.

Stealthy Backdoor Attack to Real-world Models in Android Apps Backdoor attacks against transfer learning with pre-trained deep learn- ing models,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:35:26.911344Z

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.

source=pdf_text observed=2026-08-10T22:35:25.933827Z digest=sha256:e55d36d7cc269a821733b2f44f8b9406c1f59bb1648b3623977622cddc268709

Observation 655e0d6d-cd04-4b4d-b86b-9e7fb0b91f0e · outbound

This paper cites Backdooring convolutional neural net- works via targeted weight perturbations,.

Stealthy Backdoor Attack to Real-world Models in Android Apps Backdooring convolutional neural net- works via targeted weight perturbations,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:35:26.893779Z

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.

source=pdf_text observed=2026-08-10T22:35:25.939409Z digest=sha256:72278e7a9aa41c13c33f4155103d040de79f4a4c0825e9a449d379c034cc4cfb

Observation a4ea0323-851b-470e-9ea6-60db1b78a687 · outbound

This paper cites Tbt: Targeted neural network attack with bit trojan,.

Stealthy Backdoor Attack to Real-world Models in Android Apps Tbt: Targeted neural network attack with bit trojan,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:35:26.873171Z

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.

source=pdf_text observed=2026-08-10T22:35:25.945069Z digest=sha256:f229f7e54672ba9f219f1ca349bd9daffde203231b935e7cd6b55b0b7e0d2975

Observation 67dd8d31-044e-467e-92ba-1b9b0f092429 · outbound

This paper cites An embarrassingly simple approach for trojan attack in deep neural networks,.

Stealthy Backdoor Attack to Real-world Models in Android Apps An embarrassingly simple approach for trojan attack in deep neural networks,

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-10T22:35:25.955005Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:35:25.955005Z digest=sha256:a6e08531b3886156b0e749fa0cdfbbae3e21d0738ce8f80cd05ccf0aaa07da91

Observation 489806a7-c096-41df-8516-a06599a052bb · outbound

This paper cites Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning.

Stealthy Backdoor Attack to Real-world Models in Android Apps Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-10T22:35:25.960261Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:35:25.960261Z digest=sha256:7314acebc79aa30a1433c384709b85131138f16d1f70f7ceed59833c159190e5

Observation fc07caf4-04ca-4829-8856-3aee9bb358b1 · outbound

This paper cites Label-Consistent Backdoor Attacks.

Stealthy Backdoor Attack to Real-world Models in Android Apps Label-Consistent Backdoor Attacks

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-10T22:35:25.966861Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:35:25.966861Z digest=sha256:7467b8df2bc2567a5ff09043ac9edf916bffcaa2bd1413217616ab327133e02f

Observation 1fa58a73-dacd-4f5e-b018-ff3d1a24d563 · outbound

This paper cites Invisible backdoor attacks on deep neural networks via steganography and regularization,.

Stealthy Backdoor Attack to Real-world Models in Android Apps Invisible backdoor attacks on deep neural networks via steganography and regularization,

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:35:26.852777Z

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.

source=pdf_text observed=2026-08-10T22:35:25.973552Z digest=sha256:ba8bb58a2e5a842776de45a6d11954dd739906606b412d099e46e65c9c640e27

Observation 897b64a7-36f1-4119-8d3b-69aad79c4b5d · outbound

This paper cites Invisible backdoor attack with sample-specific triggers,.

Stealthy Backdoor Attack to Real-world Models in Android Apps Invisible backdoor attack with sample-specific triggers,

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-10T22:35:25.978680Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:35:25.978680Z digest=sha256:db9fb476b12af9812dbb47e4f0e51fd7ebfe87751fe7fd63f090614cf66b4cce

Observation a3260270-d4d0-4fd4-b9dd-6a855567842c · outbound

This paper cites Backdoor attack with sparse and invisible trigger,.

Stealthy Backdoor Attack to Real-world Models in Android Apps Backdoor attack with sparse and invisible trigger,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:35:26.824087Z

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.

source=pdf_text observed=2026-08-10T22:35:25.984305Z digest=sha256:7455544696535b091a2137c60c405c3ae78043a0da3224da5348f11d46bfee9b

Observation 07bd4d51-2d2c-46d0-8c30-53131fa9dd75 · outbound

This paper cites Deeppayload: Black- box backdoor attack on deep learning models through neural payload injection,.

Stealthy Backdoor Attack to Real-world Models in Android Apps Deeppayload: Black- box backdoor attack on deep learning models through neural payload injection,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:35:26.807407Z

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.

source=pdf_text observed=2026-08-10T22:35:25.990210Z digest=sha256:e80191b04969202d4288012849beb2003ba031027e8ce5bac418393518bba509

Observation f3162b90-5209-43da-92ff-62c90b4f1f37 · outbound

This paper cites Stegastamp: Invisible hyperlinks in physical photographs,.

Stealthy Backdoor Attack to Real-world Models in Android Apps Stegastamp: Invisible hyperlinks in physical photographs,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:35:26.790408Z

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.

source=pdf_text observed=2026-08-10T22:35:25.996218Z digest=sha256:0da59a0d8df56c4183e25a83a6ffb07a0393447735b6c1d6d25d6f261bbd3e44

Observation 26f87ed6-9791-447d-8ff2-574555f88026 · outbound

This paper cites Deep feature space trojan attack of neural networks by controlled detoxification,.

Stealthy Backdoor Attack to Real-world Models in Android Apps Deep feature space trojan attack of neural networks by controlled detoxification,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:35:26.771303Z

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.

source=pdf_text observed=2026-08-10T22:35:26.002404Z digest=sha256:fe54b5cb3cbaadd9a8dcc9fdc977e39f96af2a129f1cf965d1d4c1c61c459b48

Observation 94824a63-d031-456e-b134-b9cb2f3435a4 · outbound

This paper cites Backdoor embedding in convolutional neural network models via invisible perturbation,.

Stealthy Backdoor Attack to Real-world Models in Android Apps Backdoor embedding in convolutional neural network models via invisible perturbation,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:35:26.751218Z

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.

source=pdf_text observed=2026-08-10T22:35:26.008850Z digest=sha256:3b47f00a3dc7c7094498903db12185e23d76721a6107dd37158fc639b557289a

Observation ce84a997-c048-4a08-a1bd-1ae7715ecc49 · outbound

This paper cites Universal adversarial perturbations,.

Stealthy Backdoor Attack to Real-world Models in Android Apps Universal adversarial perturbations,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:35:26.733731Z

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.

source=pdf_text observed=2026-08-10T22:35:26.013369Z digest=sha256:cd8e5ce6f7de2f2f3327a86bee192483e0fe779264f16b15800f72ab2256dc19

Observation a7f75fbe-29ed-469f-a17d-95fdd54c21b1 · outbound

This paper cites Backdoor attack on deep learning-based medical image encryption and decryption network,.

Stealthy Backdoor Attack to Real-world Models in Android Apps Backdoor attack on deep learning-based medical image encryption and decryption network,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:35:26.694273Z

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.

source=pdf_text observed=2026-08-10T22:35:26.023443Z digest=sha256:fa0d296822e0441c314a62f4288e7ec5e6975c36e2394f1bb37c8ec66ddb0d43

Observation 011e80a5-69c9-4f58-bea3-45e097af3d66 · outbound

This paper cites Eyeriss: A spatial architecture for energy-efficient dataflow for convolutional neural networks,.

Stealthy Backdoor Attack to Real-world Models in Android Apps Eyeriss: A spatial architecture for energy-efficient dataflow for convolutional neural networks,

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-10T22:35:26.028279Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:35:26.028279Z digest=sha256:0a1e79b85be9748b9cb96bdc7c38b0e6f0082a7053139f1e56d768c52ec69100

Observation c060de48-0ad4-4b1b-85e3-037d6f786778 · outbound

This paper cites Edge Intelligence: Architectures, Challenges, and Applications.

Stealthy Backdoor Attack to Real-world Models in Android Apps Edge Intelligence: Architectures, Challenges, and Applications

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-10T22:35:26.033145Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:35:26.033145Z digest=sha256:31e272c54e0b293d46d40306680555dca786639583a9a70acc86fb0b7c8d6741

Observation 1a3da2d6-489f-4c3d-b043-f89f5c4c1e5a · outbound

This paper cites Tensorflow hub,.

Stealthy Backdoor Attack to Real-world Models in Android Apps Tensorflow hub,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:35:26.660531Z

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.

source=pdf_text observed=2026-08-10T22:35:26.039683Z digest=sha256:92d4e19f29c6590a0b9d440bdc69015ad61e6359ead4adfb1834d131b9a4a33f

Observation d0e90df5-0154-4983-b200-99b6fe70992c · outbound

This paper cites an unresolved cited work.

Stealthy Backdoor Attack to Real-world Models in Android Apps Unresolved cited work

Reference 42

Resolution
unresolved
raw_fallback, observed 2026-08-10T22:35:26.639352Z

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.

source=pdf_text observed=2026-08-10T22:35:26.044305Z digest=sha256:224d95b48bf97a150e352aa728e2675629959b6abe2b30e7ebf8b52bff536a0c

Observation dd7ec390-d701-465e-b021-f9e81955b482 · outbound

This paper cites Investigating white- box attacks for on-device models,.

Stealthy Backdoor Attack to Real-world Models in Android Apps Investigating white- box attacks for on-device models,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:35:26.617714Z

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.

source=pdf_text observed=2026-08-10T22:35:26.049918Z digest=sha256:1e49106550688147729e7e07501f370f8c4f44e1f4b3efee5e78c65b5525510c

Observation e70aa1f9-47c5-4aa7-a61f-5878b43fedba · outbound

This paper cites Apktool: A tool for reverse engineering android apk files.

Stealthy Backdoor Attack to Real-world Models in Android Apps Apktool: A tool for reverse engineering android apk files

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:35:26.593461Z

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.

source=pdf_text observed=2026-08-10T22:35:26.055502Z digest=sha256:74771b6beb13f75798bea6108dd65144c17dcf2d789c21b9c96e0857e3215a32

Observation fcb80719-b950-43d5-bc6e-0bab7d8b74a1 · outbound

This paper cites Defending neural backdoors via genera- tive distribution modeling,.

Stealthy Backdoor Attack to Real-world Models in Android Apps Defending neural backdoors via genera- tive distribution modeling,

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-10T22:35:26.060564Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:35:26.060564Z digest=sha256:de5087fa25f4851ac74bf01d020814dd7ee2ca6a160e31dc7cd85c6ba1e246e9

Observation 6c732795-b2d7-4304-8547-c85632d3b6a4 · outbound

This paper cites Neural cleanse: Identifying and mitigating backdoor attacks in neural networks,.

Stealthy Backdoor Attack to Real-world Models in Android Apps Neural cleanse: Identifying and mitigating backdoor attacks in neural networks,

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-10T22:35:26.066312Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:35:26.066312Z digest=sha256:96db3cba0b96cfbae4b87ccb216cc3b15f38eabe15db05d89868e78a40e43814

Observation 98bd42a0-63b5-44e4-90ab-f3031e311dec · outbound

This paper cites Sentinet: Detecting localized universal attacks against deep learning systems,.

Stealthy Backdoor Attack to Real-world Models in Android Apps Sentinet: Detecting localized universal attacks against deep learning systems,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:35:26.543955Z

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.

source=pdf_text observed=2026-08-10T22:35:26.072258Z digest=sha256:d0712dbbd18702af53c07755d1d4a5dcfa2146f564fea02a76372229385d6ac1

Observation 4203273f-9bf4-475b-baf5-6ee2c258568c · outbound

This paper cites Design and evaluation of a multi-domain trojan detection method on deep neural networks,.

Stealthy Backdoor Attack to Real-world Models in Android Apps Design and evaluation of a multi-domain trojan detection method on deep neural networks,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:35:26.524268Z

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.

source=pdf_text observed=2026-08-10T22:35:26.077414Z digest=sha256:260dfb151610a95f4f43f1df60304053af519581e117ae04313fb686653bed1e

Observation d133ea0b-358b-4272-b4c8-ef40932e8c53 · outbound

This paper cites Invisible backdoor attack with attention and steganography,.

Stealthy Backdoor Attack to Real-world Models in Android Apps Invisible backdoor attack with attention and steganography,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:35:26.505099Z

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.

source=pdf_text observed=2026-08-10T22:35:26.082945Z digest=sha256:5f98e7bca3db9a9df3191918692c9d3223c2a21d71f01d5efbedb6624ee5c2c0

Observation 887c242a-a844-42ef-abdc-88f58029fd59 · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation,.

Stealthy Backdoor Attack to Real-world Models in Android Apps U-net: Convolutional networks for biomedical image segmentation,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:35:26.487218Z

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.

source=pdf_text observed=2026-08-10T22:35:26.092202Z digest=sha256:7347cbe478496922f75602ca5d771397b20200fd2ac86ff2da17fd93e80528e6

Observation c014d7e2-eec6-47da-af34-ad24feffe2a4 · outbound

This paper cites Spa- tial transformer networks,.

Stealthy Backdoor Attack to Real-world Models in Android Apps Spa- tial transformer networks,

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:35:26.467732Z

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.

source=pdf_text observed=2026-08-10T22:35:26.100079Z digest=sha256:f95e84cc309e097333e8cd5884c1123e4cfcb5367dd40ad64accf81fd4c85d3c

Observation 49aa9ba8-62f1-4315-8f74-78ad5b2dcd62 · outbound

This paper cites Mobilenetv2: Inverted residuals and linear bottlenecks,.

Stealthy Backdoor Attack to Real-world Models in Android Apps Mobilenetv2: Inverted residuals and linear bottlenecks,

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-10T22:35:26.105981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:35:26.105981Z digest=sha256:b5faec2d9dd598b2d9213f63c36209939809b08cfe6adab5f802fdd0a7a5a26a

Observation 7a4e90ef-5726-47ed-b88e-52274a91b336 · outbound

This paper cites Learning transferable architectures for scalable image recognition,.

Stealthy Backdoor Attack to Real-world Models in Android Apps Learning transferable architectures for scalable image recognition,

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:35:26.429995Z

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.

source=pdf_text observed=2026-08-10T22:35:26.111328Z digest=sha256:f6222f4da606af6d477b28e06afb1d370a0623f85c6f48f3337fbf5831e65e3b

Observation 57f8ea9c-455d-477a-82b1-2aa0864b6046 · outbound

This paper cites Deep residual learning for image recognition,.

Stealthy Backdoor Attack to Real-world Models in Android Apps Deep residual learning for image recognition,

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-10T22:35:26.117343Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:35:26.117343Z digest=sha256:9de7e2b80a8cc4be180a3a37b652ab9a91a6289ee591d8a3e8e3d15221555721

Observation 34eaa056-e6b5-45fb-8e1b-a4ca4e0b0317 · outbound

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

Stealthy Backdoor Attack to Real-world Models in Android Apps Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-10T22:35:26.124725Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:35:26.124725Z digest=sha256:a860467638498c36a428d965fa39ababa007d8e5f051788eed57a87ef99dd29b

Observation 1ff79a83-a940-4654-a1a1-940a1288ccec · outbound

This paper cites Multiscale structural similarity for image quality assessment,.

Stealthy Backdoor Attack to Real-world Models in Android Apps Multiscale structural similarity for image quality assessment,

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:35:26.389142Z

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.

source=pdf_text observed=2026-08-10T22:35:26.132746Z digest=sha256:dcb64b72cbe2a1c6212ff18ba69376eeecab29c1087f714f38921e607e9fcc8e

Observation c1282487-bc02-4bfe-bf2a-b9847a8289ae · outbound

This paper cites an unresolved cited work.

Stealthy Backdoor Attack to Real-world Models in Android Apps Unresolved cited work

Reference 2017

Resolution
unresolved
raw_fallback, observed 2026-08-10T22:35:26.714737Z

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.

source=pdf_text observed=2026-08-10T22:35:26.018138Z digest=sha256:c8b080c6d2123a8f952da53df042b3958169c3b5c71ee997e9585aacb9cf3d1f

Observation a991a98e-e2a9-4665-ba61-a944962f8570 · outbound

This paper cites an unresolved cited work.

Stealthy Backdoor Attack to Real-world Models in Android Apps Unresolved cited work

Reference 2021

Resolution
parse uncertain
raw_fallback, observed 2026-08-10T22:35:27.223706Z

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.

source=pdf_text observed=2026-08-10T22:35:25.816519Z digest=sha256:06baee21f1f58b4b8431b4799575c6ab715f46fcc38fba2ccd7fad01e1e70ea5

Pith citing papers

Observation 4e99cfdb-600b-4cbb-ad54-b7e694a6789e · inbound

SoK: Attack and Defense Landscape of Mobile On-device AI Systems cites this paper.

SoK: Attack and Defense Landscape of Mobile On-device AI Systems Stealthy Backdoor Attack to Real-world Models in Android Apps

Reference 56

Resolution
verified exact
arxiv_id, observed 2026-07-02T11:46:54.740085Z

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.

source=pdf_text observed=2026-07-02T11:45:33.273144Z digest=sha256:e8523efa57c924ce054f7c57f94414e09041b5f55a2553ad7690406727e59b41