Paper Citation Record · LEDGER

Phishing URL Detection using Bi-LSTM

As of 19 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 0 inbound Pith citation observations for arXiv:2504.21049.

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

pith.paper-citation-record.v1
2504.21049 v1

Coverage vector

measured 12 of 12 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:32:56.805137Z

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

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

measured 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

12 of 12 outbound references displayed

verified exact7
verified fuzzy4
unresolved0
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d01e3f67-2186-4553-8cc4-39fb71dc19fc · outbound

This paper cites Phishingrtds: A real-time detection system for phishing attacks using a deep learning model,.

Phishing URL Detection using Bi-LSTM Phishingrtds: A real-time detection system for phishing attacks using a deep learning model,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:32:57.040562Z

Source-reported events for the cited work

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

Observation 32b3e0fe-5877-4cd1-8b1d-201eab879c01 · outbound

This paper cites Phishing url detection with neural networks: an empirical study,.

Phishing URL Detection using Bi-LSTM Phishing url detection with neural networks: an empirical study,

Reference 2

Resolution: malformed identifier; raw_fallback, observed 2026-08-16T05:32:57.023988Z

Source-reported events for the cited work

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

Observation 1f1278ea-f5bf-4db3-b61b-399c8b53ec70 · outbound

This paper cites Enhanced phishing url detection using a novel gru-cnn hybrid approach,.

Phishing URL Detection using Bi-LSTM Enhanced phishing url detection using a novel gru-cnn hybrid approach,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:32:57.008449Z

Source-reported events for the cited work

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

Observation 062bff88-f2fe-4628-aeba-0c202855dbb1 · outbound

This paper cites An integrated csppc and bilstm frame- work for malicious url detection,.

Phishing URL Detection using Bi-LSTM An integrated csppc and bilstm frame- work for malicious url detection,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:32:56.992672Z

Source-reported events for the cited work

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

Observation db012605-12ae-4ed5-b384-bb69e9ca4cec · outbound

This paper cites Phishing url detection using bi-lstm with attention mecha- nism,.

Phishing URL Detection using Bi-LSTM Phishing url detection using bi-lstm with attention mecha- nism,

Reference 5

Resolution: verified exact; doi, observed 2026-08-16T05:32:56.875960Z

Source-reported events for the cited work

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

Observation aa407080-7f67-4692-878e-28e4b0d46423 · outbound

This paper cites A Sophisticated Framework for the Accurate Detection of Phishing Websites.

Phishing URL Detection using Bi-LSTM A Sophisticated Framework for the Accurate Detection of Phishing Websites

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-08-16T05:32:56.959474Z

Source-reported events for the cited work

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

Observation 25020608-44d5-407b-84f0-58fb610826df · outbound

This paper cites Url based phishing attack detection using bilstm-gated highway attention block convolutional neural network,.

Phishing URL Detection using Bi-LSTM Url based phishing attack detection using bilstm-gated highway attention block convolutional neural network,

Reference 7

Resolution: verified exact; doi, observed 2026-08-16T05:32:56.858099Z

Source-reported events for the cited work

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

Observation 7ba493a0-89e1-4ac6-a028-762feaab260d · outbound

This paper cites Enhancing Phishing Detection through Feature Importance Analysis and Explainable AI: A Comparative Study of CatBoost, XGBoost, and EBM Models.

Phishing URL Detection using Bi-LSTM Enhancing Phishing Detection through Feature Importance Analysis and Explainable AI: A Comparative Study of CatBoost, XGBoost, and EBM Models

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-08-16T05:32:56.936920Z

Source-reported events for the cited work

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

Observation 2f3cb1db-4eae-4222-9c1e-328253a2f8d3 · outbound

This paper cites PhishGuard: A Convolutional Neural Network Based Model for Detecting Phishing URLs with Explainability Analysis.

Phishing URL Detection using Bi-LSTM PhishGuard: A Convolutional Neural Network Based Model for Detecting Phishing URLs with Explainability Analysis

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-08-16T05:32:56.914302Z

Source-reported events for the cited work

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

Observation 622ed3ed-e86c-4f48-ad5a-6a146d45e92f · outbound

This paper cites Phishing url detection using bilstm with attention mechanism,.

Phishing URL Detection using Bi-LSTM Phishing url detection using bilstm with attention mechanism,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:32:56.976394Z

Source-reported events for the cited work

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

Observation 0ed73be2-f8c9-4f81-bc12-bdc1b9a7231b · outbound

This paper cites Available: https://doi.org/10.4018/979-8-3693-7540-2.

Phishing URL Detection using Bi-LSTM Available: https://doi.org/10.4018/979-8-3693-7540-2

Reference 184

Resolution: verified exact; doi, observed 2026-08-16T05:32:56.841220Z

Source-reported events for the cited work

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

Observation c193c5d3-b0dc-4b68-a513-cb6c92845bb5 · outbound

This paper cites Available: https://doi.org/10.1038/s41598-025-91148-z.

Phishing URL Detection using Bi-LSTM Available: https://doi.org/10.1038/s41598-025-91148-z

Reference 2025

Resolution: verified exact; doi, observed 2026-08-16T05:32:56.892097Z

Source-reported events for the cited work

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

Pith citing papers

No inbound Pith citation observations are available.