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Paper Citation Record · LEDGER

Time Series Based Network Intrusion Detection using MTF-Aided Transformer

As of 19 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:2508.16035.

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

pith.paper-citation-record.v1
2508.16035 v1

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T17:38:39.790786Z

measured 16 of 16 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

16 of 16 outbound references displayed

  • verified exact0
  • verified fuzzy14
  • unresolved2
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 42c0e7c7-86e9-40ea-889c-0b4dbeed566e · outbound

This paper cites Software-defined networking: A comprehensive survey,.

Time Series Based Network Intrusion Detection using MTF-Aided Transformer Software-defined networking: A comprehensive survey,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:38:43.101524Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-05T17:38:37.863238Z digest=sha256:87104810e71ebc13834b2193a5775738c562aa07752ecf793215e43f41571b94

Observation 35b85d22-da35-4a9e-9078-4bbc4232e4f5 · outbound

This paper cites Sdn security review: Threat taxonomy, implications, and open challenges,.

Time Series Based Network Intrusion Detection using MTF-Aided Transformer Sdn security review: Threat taxonomy, implications, and open challenges,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:38:42.636405Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-05T17:38:37.979242Z digest=sha256:14e1edfbdd4f7cf550ff162dc9cfab305f49b712a3593b89f10a08287533eabc

Observation c4904266-a7d1-4f9d-a35b-eeaa4548675d · outbound

This paper cites An enhanced resilient backpropagation artificial neural network for intrusion detection system,.

Time Series Based Network Intrusion Detection using MTF-Aided Transformer An enhanced resilient backpropagation artificial neural network for intrusion detection system,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:38:42.265316Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-05T17:38:38.059598Z digest=sha256:2a7b0c1744a5ac80bd2a7243724c617ffd2e1fc8ae4f9c64e50edc8dce38dfa5

Observation 33d5edcb-e178-4a68-9bb6-2fd9bdf75cdc · outbound

This paper cites Enhanced network intrusion detection using deep convolutional neural networks,.

Time Series Based Network Intrusion Detection using MTF-Aided Transformer Enhanced network intrusion detection using deep convolutional neural networks,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:38:42.018984Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-05T17:38:38.153584Z digest=sha256:1012a7bceae71f0cdfb104b459486256f3c7cb712470051d3b5fe8935468356b

Observation 38d24e18-3412-476d-96ad-6d3d2701bbc0 · outbound

This paper cites Network intrusion detection via flow-to-image conversion and vision transformer classification,.

Time Series Based Network Intrusion Detection using MTF-Aided Transformer Network intrusion detection via flow-to-image conversion and vision transformer classification,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:38:41.791835Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-05T17:38:38.235116Z digest=sha256:383ed21a569cb24a809c589c756137326f2a6190f2538431149204f37c888188

Observation d24c5901-e1a1-4445-952e-aaf0b9ccbc0f · outbound

This paper cites A convolutional neural network for improved anomaly-based network intrusion detection,.

Time Series Based Network Intrusion Detection using MTF-Aided Transformer A convolutional neural network for improved anomaly-based network intrusion detection,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:38:41.583319Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-05T17:38:38.305712Z digest=sha256:f2b513747151f666e4f943ca266ee3c5cb71b5bd35d96b67be9e8594f126811f

Observation c9398546-9eb8-49cd-8734-99aaba099366 · outbound

This paper cites A novel approach for network intrusion detection using multistage deep learning image recognition,.

Time Series Based Network Intrusion Detection using MTF-Aided Transformer A novel approach for network intrusion detection using multistage deep learning image recognition,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:38:41.344269Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-05T17:38:38.484914Z digest=sha256:db93794276ad5eeeea73733e9f7e6bf0d1861b93e677bbf9e6f5ac56b75dd670

Observation 71ade03c-a35a-4001-9398-4d00bf54d04a · outbound

This paper cites Deep learning for anomaly detection in time-series data: Review, analysis, and guidelines,.

Time Series Based Network Intrusion Detection using MTF-Aided Transformer Deep learning for anomaly detection in time-series data: Review, analysis, and guidelines,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:38:41.176061Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-05T17:38:38.643997Z digest=sha256:a5a8460bf2dd78fd3e255cfaf10d372475595873dd48379457e96ab3555e228a

Observation 7d16476a-b815-4f21-aeb2-c56202158b88 · outbound

This paper cites Time Series Anomaly Detection Using Convolutional Neural Networks and Transfer Learning.

Time Series Based Network Intrusion Detection using MTF-Aided Transformer Time Series Anomaly Detection Using Convolutional Neural Networks and Transfer Learning

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-05T17:38:38.816466Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T17:38:38.816466Z digest=sha256:f47efbec27e865e66ea4d9eba71958c9bb847e5b4bab3d3778240a08ab9b65f2

Observation 62cc930d-a541-4ad4-8eca-190b38f8aeb3 · outbound

This paper cites An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling.

Time Series Based Network Intrusion Detection using MTF-Aided Transformer An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-05T17:38:38.979060Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T17:38:38.979060Z digest=sha256:99a4d9a34d6245f4ec0bfce5fecf2c11c55b82a75102ebc8d2038163c8e9bd9f

Observation f5daba24-f367-4338-9aba-6baa24995ed7 · outbound

This paper cites An attention- based convlstm autoencoder with dynamic thresholding for unsupervised anomaly detection in multivariate time series,.

Time Series Based Network Intrusion Detection using MTF-Aided Transformer An attention- based convlstm autoencoder with dynamic thresholding for unsupervised anomaly detection in multivariate time series,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:38:40.987006Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-05T17:38:39.101447Z digest=sha256:452c2ab750ce5257c0a8b92ef07b181651996ddc54b72bf3cc6e33c4ca31a887

Observation 7b273e73-91f0-4d53-b12c-bcfaee4cc209 · outbound

This paper cites Insdn: A novel sdn intrusion dataset,.

Time Series Based Network Intrusion Detection using MTF-Aided Transformer Insdn: A novel sdn intrusion dataset,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:38:40.818682Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-05T17:38:39.206446Z digest=sha256:98c889ebb3536719b1992e19984901e44de9195a870073fe15bc5e0d8d0481c9

Observation 9e620a03-be57-42c3-b545-d43fc728f588 · outbound

This paper cites Efficient knn classi- fication with different numbers of nearest neighbors,.

Time Series Based Network Intrusion Detection using MTF-Aided Transformer Efficient knn classi- fication with different numbers of nearest neighbors,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:38:40.611449Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-05T17:38:39.305668Z digest=sha256:5a3a3e7c36946d15b1303f7d44f967a46ffd7c48cc13a313b492595c789610cf

Observation 39b1e54f-6a2e-49b5-95f5-f5979c717025 · outbound

This paper cites Random forest in remote sensing: A review of applications and future directions,.

Time Series Based Network Intrusion Detection using MTF-Aided Transformer Random forest in remote sensing: A review of applications and future directions,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:38:40.424314Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-05T17:38:39.386913Z digest=sha256:47a7ad8f0ef4e124e53c46830e68e03705f32b665ff8a05d411093ff093bbe56

Observation 6eca9b0f-825a-4b98-9a83-2dc13b526284 · outbound

This paper cites Network anomaly detection using lstm based autoencoder,.

Time Series Based Network Intrusion Detection using MTF-Aided Transformer Network anomaly detection using lstm based autoencoder,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:38:40.213375Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-05T17:38:39.577853Z digest=sha256:4d098beaf6bad0e5a0c465734738eccbecdaa449e9e1815b27ab19d4d4b29756

Observation 6dd257c8-56ca-4068-8ebd-8e21c405d8f5 · outbound

This paper cites Unsupervised anomaly detection via variational auto-encoder for seasonal kpis in web applications,.

Time Series Based Network Intrusion Detection using MTF-Aided Transformer Unsupervised anomaly detection via variational auto-encoder for seasonal kpis in web applications,

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T17:38:40.003507Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-05T17:38:39.790786Z digest=sha256:69fa7f587b1ce4f4908b97f16b71f6ad2961ef4e9c8355aabef03e4d3e1f6ade

Pith citing papers

No inbound Pith citation observations are available.