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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 2026-08-18T06:34:40.430872+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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:35:25.791905Z digest=sha256:4fc05e72612eb7bfb8c11a3785749316033ac25f97a3b235954a72effe20dbff

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:35:25.799022Z digest=sha256:f7602f967ba21697d4fcf651ab675a6be72c2645170b0bd39cfae905f5b7637b

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:35:25.804567Z digest=sha256:f84eb9eb67e1110dd7f5b6376942a977e6db45d3466afb7056cd513b8ff1c615

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:35:25.810228Z digest=sha256:284ad90d8a96ad1aa979b9ae2d0e850b4fd25ae4f16fdad1e734acaba7fbd38e

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:35:25.821947Z digest=sha256:5346a4cb338b0dff4ca58030508f1a70095fcd867d2481a0dea89cb040a46ca7

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:35:25.828211Z digest=sha256:0c061652f1c3da54eb17cfe2911aeb93e6dba10a0499ba2f13c7ab35b451164d

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:35:25.833234Z digest=sha256:d9165008978c5ab7cc25c996333aee7fee2d2bf9a2762ea4ae5e7714ed10d6f3

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
verified fuzzy
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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:35:25.838592Z digest=sha256:0346492087a2f85f9a31bdcb75f2ed233fa7a4df8b0301c4c0e3abfd142aa188

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:35:25.843547Z digest=sha256:ace1e98a8f1eb52a230c1dd43a15bdb2eba72f90accfb261020e42c1d385997f

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:35:25.848543Z digest=sha256:fdd8b23d82e93234a77ee6e39b675c575baf8586d39438fbf7f2f2f537256d34

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:35:25.853952Z digest=sha256:6928fb8f9e24a8df72766a7af9aa7ed01a22dacb8e32ba84f5e574d8208a9a32

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:35:25.859190Z digest=sha256:0cfc94d131446a74c87787366a7d8795513b93aa0d2ffa67f8c9a5dae2154970

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:35:25.864631Z digest=sha256:dffc1da98d54f71bafc586156492d8fab4c1f2b44fe77310606e32dbd6118ee2

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:35:25.871524Z digest=sha256:e76ed7d0ec9565ffcd74aede1989a1c80849c887a3d1fa89d4997201f7259c02

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:35:25.877278Z digest=sha256:293712cc3376cc28244e6ac4c3d62c58eb656931c4e91cfede305046ee1a19ee

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:fe35e08bba7eab9f09f30bdae98f13b02388234306b105c90126ee4df393e6f8

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=sha256:9a59a348214ad03f415fbccd3d405b1b9696949c8b7bc91ddd2557ae175a050e

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:35:25.897320Z digest=sha256:0b8019f5b65d279ea2aa7a55a6287b46890fc97517fa8a819e41f057c7916c82

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=sha256:4cd00b0d74ff9c696d2ae97fc8245300043be1f2fe2fc75aa054534d804dfb8c

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:f23b87df0e9ecda522d0f5d780b6bbf5c62af7f27267e61fe6228ef70910cd0c

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=sha256:8b3ef1a7fb36a6b3c90bcd593e5f872e2503e01ebd88b00a8ad4ad61682d7ec5

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:35:25.921333Z digest=sha256:4e536501bf940e8776be626cbc0b865cc9ebe7c3a2b65c4681cc0cad4f813465

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=sha256:817731c7f509858ef966d3f8657d2b3e6ddc73b2fd5fe1f20e567e4717cecf12

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:35:25.933827Z digest=sha256:7593ef5abef91a3c8b2c1fc80c5c357c9c017aefebb88238c17eaaef22f7ca14

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:35:25.939409Z digest=sha256:b0ef46671a665b272a81f45d0b76a943f22b74b37e3ca4f0da207fd15e2d24ca

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:35:25.945069Z digest=sha256:0a4c4719f19a701b8a235ec6ec6ff660c14387058c21961f5c344574b73a7e6f

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=sha256:8a4af61773cf4dd59a68867ec3c2848e21a8b341719f9dd6a47137c9d7a66799

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=sha256:32efe1e7d1e10699ed4dab3f266d21b9b9fc1b27568580b76e8f4acbcc6a5725

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=sha256:42df95bdcc7edd453317b38f194e89095a2b39276fd8cf02cb70ff6611202896

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:35:25.973552Z digest=sha256:06dd3df2efc9010cb2740917dadf701c43b4c111e5fd3e1c2e1f7474296c9927

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=sha256:0c354ce0ad9ef7142b68fd6774e695b4f4a31c20fd3a98c106144212c6ebd38b

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:35:25.984305Z digest=sha256:bf3d449fad4d3185c128aa93c312ac4f3e7bfe51a7b49893aeab589d81af1e5b

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:35:25.990210Z digest=sha256:975ad83a39133362cf8388c9c2dbda9cc192ed382c79a1c47d278219afb30a2b

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:35:25.996218Z digest=sha256:a9db4a2eb4f3560f0d082fd79cc575123087c2db85bf7151f3e28eb8d05f9c4a

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:35:26.002404Z digest=sha256:f8df03ae0d2dba776b2458e8bdb12eeb3dfd7dc9cfe9e0db6c91db94663ecd7c

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:35:26.008850Z digest=sha256:38a24e9ad1e628d14f5d84eeb0caf37b5d28e916ff4085c768643cf8eb4c552d

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:35:26.013369Z digest=sha256:90a71cec1414cdcd8e32d6ec019a40e6184f48ad2827cb98bc785c1087d7402d

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:35:26.023443Z digest=sha256:4fa167ff73b3a9ccd2b0d038f7a308b4d42935142cb361610709b5dfa03741ec

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=sha256:612b751a95df0128f329123113c7b5d81eab0c9d7276182df38c0e082d1b40af

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=sha256:64cbbf54c463c7558774044200f3e3378b5a38b4bc86204a9aad543880807dc3

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:35:26.039683Z digest=sha256:5c795c9385feaf6647e6a376236d1cb0940f6bbaefba3f4c3e631fa2c8b93d5f

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:35:26.044305Z digest=sha256:29dc7b8f9e768d36c45efc710259962ff15ca7b73a0ccdc50ad89b708675c626

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:35:26.049918Z digest=sha256:62bffffb2dfc69bbe08ec71f4fe71aecf0c46ea0402f6b84e5944b57dc75b5d7

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:35:26.055502Z digest=sha256:563fb142bcece899b5691060b9ad1f644b2a9ca96306f118a0db28b3652ca276

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=sha256:5ce816e7c51ce30f9f65e6f5096bfc2e5ca60d2fde6ccf52bfdd4f43e5bce5ca

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=sha256:2ff639437a84949c17d409a96c5bffbebe568f5b0c1eaa9a7a5fe1e2284479a6

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:35:26.072258Z digest=sha256:889ed6c78c9189d5e763b092a2751a678848fc83d9054a0011cf39773901da32

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:35:26.077414Z digest=sha256:15bd00526e872d60671060fae4d70fe742bc580c2e147cbaa3ed4fc61794fe60

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:35:26.082945Z digest=sha256:a6adf5f1ebff77329a831dae50fd82252dc8ebd97b8baa607faa698222774a7d

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:35:26.092202Z digest=sha256:92fedd9c081e6bdf904d62c14acc1d4a92796eb8a3669cee04880e3505777a7e

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:35:26.100079Z digest=sha256:e4a27b26d28405b886eaae023fc952d91844c957bf596c9675a864acd548a089

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=sha256:5e5120bb7c61ff1b8a2f65a2f9fbac12c28dabc418731a153c58de690a077614

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:35:26.111328Z digest=sha256:f959a6d75020733bf5ce30c148473f450f5a76c015110bc639e9a632ab3d2486

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=sha256:0b8a4783947cc65712dbaee43291faf5662e0465ea0c7eeed60e8c19334a0ff4

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:f51129c4c9b48cd156440e1b2768e3efde85a63b5fa561b04d49bc38c6384c08

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:35:26.132746Z digest=sha256:c8ecfab2ece6d11a4c24ca96e81f583590ca372a5e44b8ca0aebefb243d9f535

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:35:26.018138Z digest=sha256:1b50d5b9342f9537fd5e97077e27424100c0fe8ec87b8822f500609e370b00df

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:35:25.816519Z digest=sha256:2542ae145b05a81307b04d0ab6498952dd284802ec89646ac6ae910c8bfe22b1

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-07-02T11:45:33.273144Z digest=sha256:5da55c2308bbc33b2a85c17f689bf42dd240813aafabe41fbf0dd0236eaf82e3