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Paper Citation Record · LEDGER

Bridging the Gap in Phishing Detection: A Comprehensive Phishing Dataset Collector

As of 7 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 0 inbound Pith citation observations for arXiv:2509.09592.

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

pith.paper-citation-record.v1
2509.09592 v1

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T18:52:49.022921Z

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

26 of 26 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation af1d7212-a57a-40a7-844d-7516832fd155 · outbound

This paper cites Digital 2023 July Global Statshot Re- port,.

Bridging the Gap in Phishing Detection: A Comprehensive Phishing Dataset Collector Digital 2023 July Global Statshot Re- port,

Reference 1

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source=pdf_text observed=2026-08-04T18:52:48.928811Z digest=sha256:be744d51db3352b73383e388f16049b1661b048b407e989dc42f5395db6a04a5

Observation 4f4db5eb-0ee7-4ef2-9cae-18a2ce1c2b3e · outbound

This paper cites What is phishing?.

Bridging the Gap in Phishing Detection: A Comprehensive Phishing Dataset Collector What is phishing?

Reference 2

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source=pdf_text observed=2026-08-04T18:52:48.933994Z digest=sha256:97dbb4ea7dbee2cccb7135708e915844a4a7536016adab4ef6cf4be7f33cebab

Observation 6a1e8b8f-f31d-44e1-bce9-3cfee05121dd · outbound

This paper cites The 5 Biggest Phishing Scams of All Time - IT Governance Blog En,.

Bridging the Gap in Phishing Detection: A Comprehensive Phishing Dataset Collector The 5 Biggest Phishing Scams of All Time - IT Governance Blog En,

Reference 3

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source=pdf_text observed=2026-08-04T18:52:48.938295Z digest=sha256:8a3e4f8e864024599ade05d26c55aac9d863ed0443b51f3c173ad06a0223f595

Observation 1810833d-0525-46c7-84e7-1d93362b3885 · outbound

This paper cites Phishing Activity Trends Report,.

Bridging the Gap in Phishing Detection: A Comprehensive Phishing Dataset Collector Phishing Activity Trends Report,

Reference 4

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source=pdf_text observed=2026-08-04T18:52:48.942908Z digest=sha256:713f9cbbf3ad56a46e99ddead688d027e46d2defc4d8ad2c77f7bc83ad2ed24e

Observation ba155a22-7571-473e-8734-d2ef875b6594 · outbound

This paper cites Anti-phishing based on automated indi- vidual white-list,.

Bridging the Gap in Phishing Detection: A Comprehensive Phishing Dataset Collector Anti-phishing based on automated indi- vidual white-list,

Reference 5

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source=pdf_text observed=2026-08-04T18:52:48.946917Z digest=sha256:e0647b18e46d5462823348c8ac5d08973117a4231cccfcac6b57bf4a66e96436

Observation f2c32e60-02af-450d-ac56-00a4c0a97fff · outbound

This paper cites Beyond blacklists: learning to detect malicious web sites from suspicious URLs,.

Bridging the Gap in Phishing Detection: A Comprehensive Phishing Dataset Collector Beyond blacklists: learning to detect malicious web sites from suspicious URLs,

Reference 6

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source=pdf_text observed=2026-08-04T18:52:48.950793Z digest=sha256:92ae7760b748f311e7450b04b35b45caef00ecc4a266bdbd7189792181e11c4d

Observation 0ec12bae-5e60-4b9e-9aaa-2061ec660bc8 · outbound

This paper cites Cantina: a content-based approach to detecting phishing web sites,.

Bridging the Gap in Phishing Detection: A Comprehensive Phishing Dataset Collector Cantina: a content-based approach to detecting phishing web sites,

Reference 7

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source=pdf_text observed=2026-08-04T18:52:48.955012Z digest=sha256:d458ef2c075fa40bc6a4abf2cbd6965f6ebbfa7067d122be6593bdc6ea6911d8

Observation 9e486807-f7d0-41cd-b602-46f28089108a · outbound

This paper cites Phishzoo: Detecting phishing websites by looking at them,.

Bridging the Gap in Phishing Detection: A Comprehensive Phishing Dataset Collector Phishzoo: Detecting phishing websites by looking at them,

Reference 8

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source=pdf_text observed=2026-08-04T18:52:48.959111Z digest=sha256:d31d15f0f47a74519f1efd864fb5b45d98f3bdac81f4e1f9c074d73b7b441435

Observation 9d54ebc9-abf8-4218-b586-241be78db824 · outbound

This paper cites PhishAlert: An Efficient Phishing URL Detection via Hybrid Methodology,.

Bridging the Gap in Phishing Detection: A Comprehensive Phishing Dataset Collector PhishAlert: An Efficient Phishing URL Detection via Hybrid Methodology,

Reference 9

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source=pdf_text observed=2026-08-04T18:52:48.962564Z digest=sha256:82b3c1c1806339078bbaf0c691ecfb1e20aa280e5464d9e74fa41b27bf3bed7f

Observation 2528af70-a5d6-4e48-85bb-343fc6604a7f · outbound

This paper cites A machine learning based approach for phishing detection using hyperlinks information,.

Bridging the Gap in Phishing Detection: A Comprehensive Phishing Dataset Collector A machine learning based approach for phishing detection using hyperlinks information,

Reference 10

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source=pdf_text observed=2026-08-04T18:52:48.965764Z digest=sha256:24479571c61ed595ecafcbab51da1c1ef9944f6092e228096b60e72a28d65c9d

Observation b63cc9a4-01b8-4507-b12f-cbcbf5c9ae81 · outbound

This paper cites URLNet: Learning a URL Representation with Deep Learning for Malicious URL Detection.

Bridging the Gap in Phishing Detection: A Comprehensive Phishing Dataset Collector URLNet: Learning a URL Representation with Deep Learning for Malicious URL Detection

Reference 11

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source=pdf_text observed=2026-08-04T18:52:48.969525Z digest=sha256:9637de19408d7b04adb7adee1f6470ab29fda8b2ce604bfafd01d2bd6426a2c3

Observation bd538c73-85eb-4527-adcb-02178b72c0cf · outbound

This paper cites Visualphishnet: Zero- day phishing website detection by visual similarity,.

Bridging the Gap in Phishing Detection: A Comprehensive Phishing Dataset Collector Visualphishnet: Zero- day phishing website detection by visual similarity,

Reference 12

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source=pdf_text observed=2026-08-04T18:52:48.973756Z digest=sha256:3c2fbfa004af88b9aed0323a227d158d82728ef99478c708eaac6456816a15b5

Observation 7ce40c90-462d-4c90-9ce5-80906c05a94a · outbound

This paper cites Phishpedia: A hybrid deep learning based approach to visually identify phishing webpages.

Bridging the Gap in Phishing Detection: A Comprehensive Phishing Dataset Collector Phishpedia: A hybrid deep learning based approach to visually identify phishing webpages

Reference 13

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source=pdf_text observed=2026-08-04T18:52:48.977295Z digest=sha256:f3d0780859dc85f440627e0807881a977c87d6092a5f4332410ecb165fe376f7

Observation 5d211dde-a8d7-45f3-88d3-1af2e77407d1 · outbound

This paper cites Comprehensible classification models: a position paper,.

Bridging the Gap in Phishing Detection: A Comprehensive Phishing Dataset Collector Comprehensible classification models: a position paper,

Reference 14

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source=pdf_text observed=2026-08-04T18:52:48.981183Z digest=sha256:257a744027a0871a04f7e359cc7f10567d2cbb56ffa904e24d551882c0a9e8ba

Observation 6a907cc7-8cf6-474f-b9af-315bdd60628b · outbound

This paper cites Top Sites Ranking,.

Bridging the Gap in Phishing Detection: A Comprehensive Phishing Dataset Collector Top Sites Ranking,

Reference 15

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source=pdf_text observed=2026-08-04T18:52:48.984337Z digest=sha256:2e53041ffad873804f39ab34e2906e7ea33f80152cb07e313aac033a0418382c

Observation f8e35b25-aeac-43b7-8431-3db5d916d88a · outbound

This paper cites OpenPhish,.

Bridging the Gap in Phishing Detection: A Comprehensive Phishing Dataset Collector OpenPhish,

Reference 16

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source=pdf_text observed=2026-08-04T18:52:48.988326Z digest=sha256:a2abaa0d42b1759eb3988d6308ac209e64e7a4b1b50d4b1b51b21dde2be76833

Observation 3488cc88-34fb-44b2-becc-29c697b109f4 · outbound

This paper cites MillerSmiles,.

Bridging the Gap in Phishing Detection: A Comprehensive Phishing Dataset Collector MillerSmiles,

Reference 17

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source=pdf_text observed=2026-08-04T18:52:48.991823Z digest=sha256:92d1756922eecb1483f41870c0b0ada6f5019c796a9f58552509488efb23bb21

Observation 62359a6e-83c2-4c31-bdf3-cefba6877903 · outbound

This paper cites PyWebCopy, GitHub,.

Bridging the Gap in Phishing Detection: A Comprehensive Phishing Dataset Collector PyWebCopy, GitHub,

Reference 18

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source=pdf_text observed=2026-08-04T18:52:48.995066Z digest=sha256:33f3afe4352d06fe967eb0e36e92b6b536f3a298b5535b97af2b741cf762995b

Observation cacbba6e-79bf-4050-993e-5a019607b9ff · outbound

This paper cites Alexa Top Sites,.

Bridging the Gap in Phishing Detection: A Comprehensive Phishing Dataset Collector Alexa Top Sites,

Reference 19

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source=pdf_text observed=2026-08-04T18:52:48.998797Z digest=sha256:65ccb2066ee228ae1df04612c4c124a5ecf2f4d2db09a77f058e6289b43f9302

Observation 5d0b26d0-b86f-4a88-acb8-809a719c8cdb · outbound

This paper cites Common Crawl,.

Bridging the Gap in Phishing Detection: A Comprehensive Phishing Dataset Collector Common Crawl,

Reference 20

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source=pdf_text observed=2026-08-04T18:52:49.002497Z digest=sha256:db5f396fb3128420e9debccaba66a95292a3baf6340ac8bd321ead1685f1f510

Observation 050c1554-6e84-4240-bd65-3685659c0346 · outbound

This paper cites PhishTank,.

Bridging the Gap in Phishing Detection: A Comprehensive Phishing Dataset Collector PhishTank,

Reference 21

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source=pdf_text observed=2026-08-04T18:52:49.005667Z digest=sha256:11bbf76939fa19cdfadf594b2e3eb74fb255aac9208cca2cd395725c3f83b618

Observation 8962435c-b658-460b-97e4-e1773cfb8c5b · outbound

This paper cites UCI1 Benchmark Dataset,.

Bridging the Gap in Phishing Detection: A Comprehensive Phishing Dataset Collector UCI1 Benchmark Dataset,

Reference 22

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source=pdf_text observed=2026-08-04T18:52:49.009651Z digest=sha256:aed433b807e356d9462fcf4efc55135e9157a3c27a83ef4def9a79ff41497633

Observation 658a64cc-c5ad-4d73-a6dd-a6c02a1609e9 · outbound

This paper cites Mendeley,.

Bridging the Gap in Phishing Detection: A Comprehensive Phishing Dataset Collector Mendeley,

Reference 23

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source=pdf_text observed=2026-08-04T18:52:49.012982Z digest=sha256:2d51d817614a8738aa40e82d8779ba4dc3422c4f60936c83f8f72e7aa27fb4a4

Observation 37b225df-ee3e-4a41-832b-3bc7f0055639 · outbound

This paper cites Bridging the Gap in Phishing Detection: A Comprehensive Phishing Dataset Collector,.

Bridging the Gap in Phishing Detection: A Comprehensive Phishing Dataset Collector Bridging the Gap in Phishing Detection: A Comprehensive Phishing Dataset Collector,

Reference 24

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source=pdf_text observed=2026-08-04T18:52:49.016588Z digest=sha256:a6ce0b24e6d4cf345a04603b1a949bd26dac665dae5c88e5b9d96229c301b387

Observation 58762992-054b-4230-a69f-e67b129c8751 · outbound

This paper cites BeautifulSoup,.

Bridging the Gap in Phishing Detection: A Comprehensive Phishing Dataset Collector BeautifulSoup,

Reference 25

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source=pdf_text observed=2026-08-04T18:52:49.019850Z digest=sha256:6af53b279eb08baeb3a3a4a7b9b88c7ff397174466048104f8b22caa8ce6b220

Observation 0f8f0c4b-d9a7-4ccf-b116-780ede74bcc0 · outbound

This paper cites Modeling hybrid feature-based phishing websites detection using machine learning techniques,.

Bridging the Gap in Phishing Detection: A Comprehensive Phishing Dataset Collector Modeling hybrid feature-based phishing websites detection using machine learning techniques,

Reference 26

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source=pdf_text observed=2026-08-04T18:52:49.022921Z digest=sha256:e703d8ccd4fad0988249bab70c58fd0c865fe002ba9c874f0f2525fa31325517

Pith citing papers

No inbound Pith citation observations are available.