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Paper Citation Record · LEDGER

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification

As of 18 August 2026, this Paper Citation Record lists 65 of 65 outbound references and 1 inbound Pith citation observation for arXiv:2505.12106.

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

pith.paper-citation-record.v1
2505.12106 v1

Coverage vector

measured 65 of 65 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:45:14.244387Z

measured 66 of 66 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 2026-08-06T20:00:44.892647Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T20:00:45.405278Z

Reference resolution

65 of 65 outbound references displayed

  • verified exact1
  • verified fuzzy60
  • unresolved4
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5bd4c626-eb27-4085-b714-21f1b7e74983 · outbound

This paper cites Market share of mobile operating systems worldwide from 2009 to 2024, by quarter.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Market share of mobile operating systems worldwide from 2009 to 2024, by quarter

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:15.217787Z

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=2026-08-15T20:45:13.963631Z digest=sha256:12fdccbb568b261a2e72b49e01c8f7b16e2838659f459bbc84c917177c47baf5

Observation f15083cf-acea-42a1-8d8e-502bc273dd89 · outbound

This paper cites Smartphone operating system share by age group in the u.s.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Smartphone operating system share by age group in the u.s

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:15.204042Z

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=2026-08-15T20:45:13.969005Z digest=sha256:91d14c6a834f27dfcb812f8c37c83d67eebca40f2c3f33542bca7b654f29ae20

Observation ccb8a4e8-8dea-4879-bfbc-637abfad36a0 · outbound

This paper cites Mobile security index (msi) report 2023: Security threats and attacks.https://www.verizon.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Mobile security index (msi) report 2023: Security threats and attacks.https://www.verizon

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:15.189577Z

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=2026-08-15T20:45:13.973392Z digest=sha256:6b4c572cc4895b9fb0f7274c27aee269c405a88b93e860c5d5e084d04ea82c38

Observation b85052ff-4464-43ea-8091-aa09a80ba62a · outbound

This paper cites Virus-MNIST: A Benchmark Malware Dataset.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Virus-MNIST: A Benchmark Malware Dataset

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-15T20:45:13.977873Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:45:13.977873Z digest=sha256:4bd7b141b082b418b0be098a5f650c0c8c77c3d9de057e66bf3cf90477271095

Observation ded69ae6-16ed-4f60-a665-6b97b5f8a03c · outbound

This paper cites Understanding the spreading patterns of mobile phone viruses.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Understanding the spreading patterns of mobile phone viruses

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:15.175480Z

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=2026-08-15T20:45:13.982999Z digest=sha256:9c8c3c32fa7290f85ede7afa3132ee1ec38de8c25d26725acab7d4ada605346f

Observation 4ee63c6b-bf6b-4354-9814-ab8c41b1f0e8 · outbound

This paper cites Recent worms: a survey and trends.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Recent worms: a survey and trends

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:15.162127Z

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=2026-08-15T20:45:13.988184Z digest=sha256:37ea8a064a83b5e8194c609d999d626c41905dd7edede0a8091c68be45e521e4

Observation 1695cbaa-2b90-4347-80cb-cfc9f57ee2f8 · outbound

This paper cites Adware: a review.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Adware: a review

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:15.148555Z

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=2026-08-15T20:45:13.993812Z digest=sha256:6d7113e82f323e28ef021856da19a2a8e6d23a863f157c2bdb8a2b0dc6e3376d

Observation b4946de0-5ee8-4e01-920f-bc8d1aeabe95 · outbound

This paper cites An analysis of android adware.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification An analysis of android adware

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:15.134411Z

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=2026-08-15T20:45:13.997946Z digest=sha256:679087314c495b367389eeec9067f880e247dac56ed941b8c25af015058f6e21

Observation 12c780b0-05f2-4181-9bc7-b68cde159f11 · outbound

This paper cites Exploring spyware effects.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Exploring spyware effects

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:15.120260Z

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=2026-08-15T20:45:14.002226Z digest=sha256:88d900c3a7383c44c0c25dc2f73fcfb6f7a77e28c8fc1530c0ee2dfc88b786af

Observation 059e58b7-3885-44e5-ba00-b2c725bb580f · outbound

This paper cites Ransomware: A research and a personal case study of dealing with this nasty malware.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Ransomware: A research and a personal case study of dealing with this nasty malware

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:15.107101Z

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=2026-08-15T20:45:14.006595Z digest=sha256:ba706a546e726e0602fc134112b5edbcc499e297365e8ba44b53e25b3ef91807

Observation 8e71b712-8b12-4f5a-aa1e-6dffc9ebae4e · outbound

This paper cites Rootkits and their effects on information security.Information Systems Security, 16(3):164–176, 2007.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Rootkits and their effects on information security.Information Systems Security, 16(3):164–176, 2007

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:15.093036Z

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=2026-08-15T20:45:14.011166Z digest=sha256:fffbd64fc151058e94510c348a6fa79598bdd9d31fbbfc360ba414ca58a9d175

Observation 6660f7df-0fab-44b5-993e-9c7a92be8554 · outbound

This paper cites Study on computer trojan horse virus and its prevention.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Study on computer trojan horse virus and its prevention

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:15.078348Z

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=2026-08-15T20:45:14.015358Z digest=sha256:4a6b78e3bef1d99f90a90c5162499b855a3fe62440d4db97e6ee089628b5ad1c

Observation 802a279f-20ec-4fea-a0a1-f24245c86574 · outbound

This paper cites Keyloggers: silent cyber security weapons.Network Security, 2020(2):14– 19, 2020.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Keyloggers: silent cyber security weapons.Network Security, 2020(2):14– 19, 2020

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:15.064464Z

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=2026-08-15T20:45:14.019608Z digest=sha256:f1ea2538be1d516e9f5dd4a4ccf0907d477d955aee2eb6d86e72cae32f1e4851

Observation d238e323-feab-4dbc-876c-f9aa7aa0226d · outbound

This paper cites A survey of botnet and botnet detection.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification A survey of botnet and botnet detection

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:15.050130Z

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=2026-08-15T20:45:14.024104Z digest=sha256:ac4fd889f663dc6609c1be63368994bf915590c8b0190e4c211b6855fe5b51d7

Observation 5cbf5ccd-3f1e-43fc-bd58-effa361f1d59 · outbound

This paper cites A comprehensive survey on identification of malware types and malware classification using machine learning techniques.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification A comprehensive survey on identification of malware types and malware classification using machine learning techniques

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:15.036347Z

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=2026-08-15T20:45:14.028428Z digest=sha256:a9cc1fd2255e4c48e719baa1b48b202d6745856d7ac1bf89260a93879845338a

Observation 97b14579-7d34-4407-b5bc-08cf4b238f59 · outbound

This paper cites Strengthening digital signatures via randomized hashing.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Strengthening digital signatures via randomized hashing

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:15.022360Z

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=2026-08-15T20:45:14.032794Z digest=sha256:b82fd68e4765782a81678f01313eb7fe2277c13a481d826c6f21da70420d251d

Observation 0a641f1c-9e23-4176-a060-e133f2c305f2 · outbound

This paper cites Obfuscation techniques against signature-based detection: a case study.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Obfuscation techniques against signature-based detection: a case study

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:15.007717Z

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=2026-08-15T20:45:14.037331Z digest=sha256:d2458d932c493783d11f4720315c796e478723c9f8a0a0eb6788e29fd5785526

Observation 83d44367-fa78-4e5f-b1b8-a07064294b7e · outbound

This paper cites Datdroid: Dynamic analysis technique in android malware detection.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Datdroid: Dynamic analysis technique in android malware detection

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:14.992852Z

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=2026-08-15T20:45:14.041556Z digest=sha256:b78b67cd1aff327ff6c31f5cd25489397d41e6812811a730f6416533397f1007

Observation 43b8a705-6c9e-41e2-b13d-7f461a678809 · outbound

This paper cites A systematic literature review of android malware detection using static analysis.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification A systematic literature review of android malware detection using static analysis

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:14.978090Z

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=2026-08-15T20:45:14.045720Z digest=sha256:214425ba2981bc8c2da0fec6cb02b21b0a9f7273f3cfeb7d96d2918d69cbe3e0

Observation 79ffaa16-32a9-4d59-9616-cf9787cc5c7f · outbound

This paper cites Behavior analysis of malware using machine learning.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Behavior analysis of malware using machine learning

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:14.962734Z

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=2026-08-15T20:45:14.049994Z digest=sha256:38a872a4f8e8eb492b011258309dbd2fbdf9f582df5fb954861a91edc33c73eb

Observation 2d513691-9126-4aa4-899f-78996f22146a · outbound

This paper cites Sequential digital signatures for cryptographic software-update authenti- cation.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Sequential digital signatures for cryptographic software-update authenti- cation

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:14.949168Z

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=2026-08-15T20:45:14.053949Z digest=sha256:e79813c96a18a8b292a95490dca8892cb58ebebf39c300cd11beeb78263054f0

Observation c65901e6-e4c1-4e57-97b2-4425d98ee2aa · outbound

This paper cites A study on malware and malware detection techniques.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification A study on malware and malware detection techniques

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:14.935112Z

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=2026-08-15T20:45:14.058286Z digest=sha256:6c97146baeef6dfb8149a858f989b0578d59fc8ca5b7d26743933a9ce4c42faf

Observation 4fdaa355-0b7b-41f0-8515-2d4371b79a15 · outbound

This paper cites Obfuscation- resilient android malware analysis based on complementary features.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Obfuscation- resilient android malware analysis based on complementary features

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:14.920584Z

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=2026-08-15T20:45:14.062551Z digest=sha256:9d62384632be0cb5e6e61735ec378061e399172c08a1bd88a0f0343c78a24f15

Observation a57f1da0-7c30-4f85-8dcf-554924386bbc · outbound

This paper cites The rise of obfuscated android malware and impacts on detection methods.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification The rise of obfuscated android malware and impacts on detection methods

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:14.906144Z

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=2026-08-15T20:45:14.066398Z digest=sha256:85661f5ff7d72436e79190adf56e38c0dd873d881a7de5b34d81b0ef2e79541f

Observation 419bb6ff-9650-4494-8595-ec0383c07128 · outbound

This paper cites Malgene: Automatic extraction of malware analysis evasion signature.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Malgene: Automatic extraction of malware analysis evasion signature

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:14.891558Z

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=2026-08-15T20:45:14.070322Z digest=sha256:c0729257ab39d85c7fc312551972e3595833a333c41c1d565ffc34fae4aba261

Observation 5c85d958-6d0b-4a23-8f1f-479a7a890b67 · outbound

This paper cites An approach to dynamic malware analysis based on system and application code split.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification An approach to dynamic malware analysis based on system and application code split

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:14.876094Z

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=2026-08-15T20:45:14.074377Z digest=sha256:6355f1ae6e3322571af5d19d4edd08383ed924f8ba7a880f891cfe9a3782cb1a

Observation 5d8544e9-bfa2-4962-9c80-f0b26332eb35 · outbound

This paper cites Nmal-droid: network- based android malware detection system using transfer learning and cnn-bigru ensemble.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Nmal-droid: network- based android malware detection system using transfer learning and cnn-bigru ensemble

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:14.861368Z

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=2026-08-15T20:45:14.078235Z digest=sha256:3fdb88ebc89a5377d845cd935d6a61b440daecbd2df4f5e6c8141952ca4e4b9d

Observation a4310238-5a56-408c-8bca-006eafbd1f7f · outbound

This paper cites Malware detection approach based on artifacts in memory image and dynamic analysis.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Malware detection approach based on artifacts in memory image and dynamic analysis

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:14.846464Z

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=2026-08-15T20:45:14.082315Z digest=sha256:24fba579af280e85b33f0ebaaf9b4a80e3837043a831d60dce6c2de8be10b51c

Observation b23dda90-6937-4992-bea9-b6af96255b13 · outbound

This paper cites A new approach to android malware detection using fuzzy logic-based simulated annealing and feature selection.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification A new approach to android malware detection using fuzzy logic-based simulated annealing and feature selection

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:14.830268Z

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=2026-08-15T20:45:14.086647Z digest=sha256:f4c5903c8f655c72aba3972b0553264b44c18de881291c68279cb749186c51c1

Observation 3bb19c9d-895c-4124-b9e5-e90312cbb1b0 · outbound

This paper cites Potential of the dynamic approach to data analysis.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Potential of the dynamic approach to data analysis

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:14.814609Z

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=2026-08-15T20:45:14.091189Z digest=sha256:fb143e2c3619447d5c13942edf3d6e2d4fe48064d7ad6551d59191b1589716ad

Observation 05019582-436f-427d-96fe-87cb8440c22a · outbound

This paper cites Malware detection in android based on dynamic analysis.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Malware detection in android based on dynamic analysis

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:14.799518Z

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=2026-08-15T20:45:14.095431Z digest=sha256:2646bca32bda9d64b96efbf671ff5c7106786ec129d744935f7c8dd08e348d07

Observation 6b5b3a63-666c-4186-87c9-489db62b813f · outbound

This paper cites Integrated static analysis for malware variants detection.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Integrated static analysis for malware variants detection

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:14.784886Z

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=2026-08-15T20:45:14.099792Z digest=sha256:3f61491765f1e5e75bb2aa25847eb00b6cde3bd1055df51d28991725524104dd

Observation 5f848853-0283-465d-a43a-cf55dba0fd7d · outbound

This paper cites A Large-Scale Database for Graph Representation Learning.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification A Large-Scale Database for Graph Representation Learning

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-15T20:45:14.103994Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:45:14.103994Z digest=sha256:e0d79f041022fe5ac5d1f7be4b456bf107bf86272cdc982109b805e2cc54ca30

Observation 70e64b02-2e92-4482-ab9c-b10628432c3c · outbound

This paper cites Hit4mal: Hy- brid image transformation for malware classification.Transactions on Emerging Telecommunications Technologies, 31(11):e3789, 2020.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Hit4mal: Hy- brid image transformation for malware classification.Transactions on Emerging Telecommunications Technologies, 31(11):e3789, 2020

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:14.769678Z

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=2026-08-15T20:45:14.108512Z digest=sha256:ed7368a73bdcfa49fbf71617272ee2c581c878c1ba6bacfa3172a6812566c9e1

Observation fb1ed3b9-6b6b-439c-a050-d0d9da4385f7 · outbound

This paper cites Dynamic security analysis on android: A systematic literature review.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Dynamic security analysis on android: A systematic literature review

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:14.753363Z

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=2026-08-15T20:45:14.113002Z digest=sha256:ff9693abeb76835ff5c3e0f7834f126aa64b2db0ec6acefef6367347cdc4d4c2

Observation 7607d515-19a9-45c3-91fa-d40c601fff85 · outbound

This paper cites Image visualization based malware detection.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Image visualization based malware detection

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:14.737950Z

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=2026-08-15T20:45:14.117016Z digest=sha256:980e6af84583a732f7b8016bc7cd7042d5c7c8bf9516e0c5586286243c2b2ff5

Observation e6ca8f5f-696b-41ef-884c-04ce63f2394c · outbound

This paper cites Improving android malware detection with entropy bytecode-to-image encoding framework.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Improving android malware detection with entropy bytecode-to-image encoding framework

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:14.722783Z

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=2026-08-15T20:45:14.121149Z digest=sha256:8df0c372048b329de702d867db79d553e7af84c05b3fde59c06ea3a059babf8b

Observation f5b6a386-4bf5-4c8a-8ac5-e69bb08c7bb2 · outbound

This paper cites Euphony: harmonious unification of cacophonous anti-virus vendor labels for android malware.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Euphony: harmonious unification of cacophonous anti-virus vendor labels for android malware

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:14.707576Z

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=2026-08-15T20:45:14.125434Z digest=sha256:8247dd87b6992c99fac74b78f0edcdb14bd70014f304827b61e8952447dc828d

Observation df5fc45a-2006-4ced-82b7-5f3d232c99c3 · outbound

This paper cites https://www.virustotal.com.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification https://www.virustotal.com

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:14.691202Z

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=2026-08-15T20:45:14.129773Z digest=sha256:ac4b3f6a9d7c3b204bf22224e2c62a36903c6f722d943a2fe2da2e4b4792d546

Observation d9effebf-163a-462a-bc55-9adcb251be73 · outbound

This paper cites Convolutional neural network: a review of models, methodologies and applications to object detection.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Convolutional neural network: a review of models, methodologies and applications to object detection

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-15T20:45:14.133832Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:45:14.133832Z digest=sha256:a811d72f1a0d6d60cdfcb7a8ad08d5129ad38416add0179e153206205939f412

Observation 1d64282a-3b4b-49c4-91de-cf470609565b · outbound

This paper cites A survey on deep learning-based lane detection algorithms for camera and lidar.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification A survey on deep learning-based lane detection algorithms for camera and lidar

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:14.665141Z

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=2026-08-15T20:45:14.138315Z digest=sha256:4608b386d30fefc2deed4113c6c83a8b3a9a870bfb12140ddbc1cd2d5c579520

Observation d1ad85b2-2374-4993-a567-3b2a6212b58f · outbound

This paper cites D-ddpm: Deep denoising diffusion probabilistic models for lesion segmentation and data generation in ultrasound imaging.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification D-ddpm: Deep denoising diffusion probabilistic models for lesion segmentation and data generation in ultrasound imaging

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:14.649703Z

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=2026-08-15T20:45:14.142540Z digest=sha256:59f6388652b2dc92ae2feadfc368a45126a44b1c95c6ecf53fd1c8d33e1ec142

Observation 96e50b04-abc8-49d3-9b18-71274ee9e170 · outbound

This paper cites Anomaly detection for in-vehicle network using cnn-lstm with attention mechanism.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Anomaly detection for in-vehicle network using cnn-lstm with attention mechanism

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:14.635058Z

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=2026-08-15T20:45:14.146844Z digest=sha256:42836eed7db96ab1b051a24da41204a5b3b258991a4b231641ceb5b8bd5bf51e

Observation 963e4144-5ca8-4057-9193-9a245f474bb1 · outbound

This paper cites Androzoo: Collecting millions of android apps for the research community.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Androzoo: Collecting millions of android apps for the research community

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:14.620002Z

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=2026-08-15T20:45:14.150886Z digest=sha256:c0eb4c836f280fb8db8e09d5acd87e18180d10f0a0886ab315a3aba6955bce45

Observation 01b3e883-a6c2-4c76-bd57-b14735ea1998 · outbound

This paper cites Drebin: Effective and explainable detection of android malware in your pocket.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Drebin: Effective and explainable detection of android malware in your pocket

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-15T20:45:14.155105Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:45:14.155105Z digest=sha256:11bcc910fb6152e8d890c6640ef4ea5f11e9ab39beaf3bfbf81d4cb079f5e481

Observation da24e4bf-ecd5-4a59-9da2-04708415b44b · outbound

This paper cites Malnet: A large-scale image database of malicious software.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Malnet: A large-scale image database of malicious software

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:14.595201Z

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=2026-08-15T20:45:14.159596Z digest=sha256:41e855efb89062ca4fa5051915b315b1c1c96036b0aa32c10572c2d57aa0a47a

Observation e9fe1242-dceb-4773-9fae-54bda259b587 · outbound

This paper cites A pe header-based method for malware detection using clustering and deep embedding techniques.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification A pe header-based method for malware detection using clustering and deep embedding techniques

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:14.581187Z

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=2026-08-15T20:45:14.164078Z digest=sha256:a34203897f7d482ad1047e641802996a6bdd35e6d1cfae004599acb4575e2710

Observation 72c5ad82-4de7-4db0-bedb-ab6fc69c66ed · outbound

This paper cites Malware images: visualization and automatic classification.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Malware images: visualization and automatic classification

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:14.567759Z

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=2026-08-15T20:45:14.168571Z digest=sha256:43cb7860a523b9cd85a6e9d48011c9d28ef6c73dac209981789c2f4e3132949a

Observation 5d578b4d-0538-4c46-b8b4-3813b293a7aa · outbound

This paper cites SoK: Leveraging Transformers for Malware Analysis.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification SoK: Leveraging Transformers for Malware Analysis

Reference 49

Resolution
verified exact
local_arxiv, observed 2026-08-15T20:45:14.288926Z

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=2026-08-15T20:45:14.173064Z digest=sha256:d23951021fd7fafb9c911e830499a2a4776947df3ffdf92bfcb74fbb467075bc

Observation 87d2a8d0-7bdc-4fe9-ae26-1839567008f1 · outbound

This paper cites An- drodex: Android dex images of obfuscated malware.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification An- drodex: Android dex images of obfuscated malware

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:14.553959Z

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=2026-08-15T20:45:14.178008Z digest=sha256:d22be70b2039a6e4d83db7692e89884675b36070bd1ea1708b373da8e6dea551

Observation 06d23b9e-f295-4937-81a1-ecb3d1148422 · outbound

This paper cites Malware classification with deep convolutional neural networks.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Malware classification with deep convolutional neural networks

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:14.539821Z

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=2026-08-15T20:45:14.182892Z digest=sha256:1ef2d42149571c096b2e38c6ab6906d637c4d18a71616be3e52e3a65c9626e91

Observation 467f8867-3392-4d71-9f3c-017a9d36ba4a · outbound

This paper cites Microsoft malware classification challenge (big 2015).

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Microsoft malware classification challenge (big 2015)

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:14.525751Z

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=2026-08-15T20:45:14.187387Z digest=sha256:7de16e8de23254588fdafe57f65053e878bb2f6432837a95e9cc974d62e73a2e

Observation 82181bdc-1da4-4ef0-9d81-ec4408421990 · outbound

This paper cites Advandmal: Adversarial training for android malware detection and family classification.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Advandmal: Adversarial training for android malware detection and family classification

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:14.511142Z

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=2026-08-15T20:45:14.192034Z digest=sha256:add01ad41ab45203c415e1b8b2f49bcf3c5a4a94e15ef04ae47127b12b28cbbe

Observation a00d960f-d1f4-4d14-a3bb-55b94af035b6 · outbound

This paper cites Android malware detection based on image-based features and machine learning techniques.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Android malware detection based on image-based features and machine learning techniques

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:14.496183Z

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=2026-08-15T20:45:14.196779Z digest=sha256:0cd78562205994ee939fa1e3409ddf14237cf9aa2e058d03783b451cdfb45264

Observation 8b4fdf0c-62dd-4e88-a1a9-d44b3301b2b2 · outbound

This paper cites Dexray: a simple, yet effective deep learning approach to android malware detection based on image representation of bytecode.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Dexray: a simple, yet effective deep learning approach to android malware detection based on image representation of bytecode

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:14.482058Z

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=2026-08-15T20:45:14.200852Z digest=sha256:06e64d0a03507ab540b28703f15dbce302c1cdd2de2cc94941d282814cf7d985

Observation 49ef1ff5-ac47-4ab3-a0ec-37a8ed8f92b9 · outbound

This paper cites A novel malware detection and family classifi- cation scheme for iot based on deam and densenet.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification A novel malware detection and family classifi- cation scheme for iot based on deam and densenet

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:14.467014Z

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=2026-08-15T20:45:14.205216Z digest=sha256:8fec5a984c6e7fff257c9936611c46f9dc7aa11a08cf9b521e813747ee704b73

Observation 9f77fc8e-f8f6-40ca-bf87-eb87e8ef990b · outbound

This paper cites Rgb-based android malware detection and classification using convolutional neural network.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Rgb-based android malware detection and classification using convolutional neural network

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:14.452399Z

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=2026-08-15T20:45:14.209435Z digest=sha256:85d864b4f01b86fc195164b1a24e071bd8ccc4034bddf8a4a3be711c2438847d

Observation 87053aac-24cf-4541-9452-b47810b6d9b5 · outbound

This paper cites Malssl–self-supervised learning for accurate and label-efficient malware classification.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Malssl–self-supervised learning for accurate and label-efficient malware classification

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:14.438019Z

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=2026-08-15T20:45:14.213586Z digest=sha256:c0646a00d0b0bd7b342827d6a4d5540303ad185e68ae32982380ffc808047600

Observation 57314408-d77a-4852-be29-c11922bbe9f2 · outbound

This paper cites Androguard tool by google.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Androguard tool by google

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:14.422331Z

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=2026-08-15T20:45:14.217597Z digest=sha256:7b66fa0c620f26dd43e4a3f334509cf910627fa6fe55d45ec8912e5e0ff31e94

Observation 2bb10e33-f93c-4a60-8c51-d901eef9d186 · outbound

This paper cites (binvis) a library for drawing space-filling curves like the hilbert curve.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification (binvis) a library for drawing space-filling curves like the hilbert curve

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:14.406531Z

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=2026-08-15T20:45:14.221692Z digest=sha256:b1d6c8315f386c65d3843bcb66d2032a8427a821e655dd056fdc0f28d68eb26a

Observation ff5c48de-72a2-40a3-add5-30469c0e6a4f · outbound

This paper cites Malgra: Machine learning and n-gram malware feature extraction and detection system.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Malgra: Machine learning and n-gram malware feature extraction and detection system

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:14.389775Z

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=2026-08-15T20:45:14.226083Z digest=sha256:a050a8b1d83bc37f2a35dffe18b7ba793d1e3aee6502323a065d7f534025a8a7

Observation f0b3b3fd-5037-4973-9db2-d216382eb5c6 · outbound

This paper cites Enhancing malware classifica- tion via self-similarity techniques.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Enhancing malware classifica- tion via self-similarity techniques

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:14.375227Z

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=2026-08-15T20:45:14.231177Z digest=sha256:379e023cbb6bc6b5a4fefe11e4628ec7c1560fa6904cb4f9f68027f23f535731

Observation 93163f84-f9ea-4376-bf5f-70f5f6f92126 · outbound

This paper cites An automated vision-based deep learning model for efficient detection of android malware attacks.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification An automated vision-based deep learning model for efficient detection of android malware attacks

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:14.361259Z

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=2026-08-15T20:45:14.235670Z digest=sha256:1d0e072c6ce6c7b141a07eaa3785c8f2cf70aad9ee8d003ecf12a6387153d367

Observation c8e1459c-2855-4902-9162-c839bc94b92c · outbound

This paper cites Machine learning with oversampling and undersampling techniques: overview study and experimental results.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Machine learning with oversampling and undersampling techniques: overview study and experimental results

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:14.347102Z

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=2026-08-15T20:45:14.240172Z digest=sha256:e6613c270467cd3da035ae501dc8e0ee14a0834c071f729eebfff331007eb6bc

Observation 2af68dcb-9146-43f5-9e95-cf0d1a2d62f3 · outbound

This paper cites Handling class imbalance problem using oversampling techniques: A review.

MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification Handling class imbalance problem using oversampling techniques: A review

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:45:14.333167Z

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=2026-08-15T20:45:14.244387Z digest=sha256:35e8d72643cf691fbe9133ed755a3f74061664c6c83e16d13a3f531ba6dd7251

Pith citing papers

Observation e1223d83-e9f5-451f-993e-08a5b40d0d22 · inbound

MalVol-25: A Diverse, Labelled and Detailed Volatile Memory Dataset for Malware Detection and Response Testing and Validation cites this paper.

MalVol-25: A Diverse, Labelled and Detailed Volatile Memory Dataset for Malware Detection and Response Testing and Validation MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification

Reference 13

Resolution
verified exact
local_arxiv, observed 2026-08-06T20:00:45.409503Z

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=2026-08-06T20:00:44.892647Z digest=sha256:23514cdeeabd3be2bc24390d1f5fc89089b09fd66fff658318e7b7b964e3d9d9