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Paper Citation Record · LEDGER

A Protocol-Language Model for Network Intrusion (Without Deep Packet Inspection)

As of 10 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 0 inbound Pith citation observations for arXiv:2606.00155.

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

pith.paper-citation-record.v1
2606.00155 v1

Coverage vector

measured 12 of 12 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-28T22:17:19.805524Z

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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 exact1
  • verified fuzzy0
  • unresolved10
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b199d004-d8dc-4e42-9561-f0b987ece565 · outbound

This paper cites CICFlowMeter: Network traffic flow generator and analyser.https://www.unb.ca/cic/research/applications.html, 2017.

A Protocol-Language Model for Network Intrusion (Without Deep Packet Inspection) CICFlowMeter: Network traffic flow generator and analyser.https://www.unb.ca/cic/research/applications.html, 2017

Reference 1

Resolution
unresolved
no resolver link, observed 2026-06-28T22:17:19.805524Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-28T22:17:19.805524Z digest=sha256:844491da59512d1a8363f8d7f4b020abf828816224ef900a932e40508df0a39a

Observation cf59a8de-c971-4d4f-9566-2e0cc2931d48 · outbound

This paper cites HTTPS encryption on the web.https://transparencyreport.google.

A Protocol-Language Model for Network Intrusion (Without Deep Packet Inspection) HTTPS encryption on the web.https://transparencyreport.google

Reference 2

Resolution
unresolved
no resolver link, observed 2026-06-28T22:17:19.805524Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-28T22:17:19.805524Z digest=sha256:9a7f167e697550b2c1f590b12dea338277dca5a087fa89b954b43daa7e9761b2

Observation 0e5e3c09-0ca5-45bd-a232-23ee1eebe249 · outbound

This paper cites Mamba: Linear-Time Sequence Modeling with Selective State Spaces.

A Protocol-Language Model for Network Intrusion (Without Deep Packet Inspection) Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 3

Resolution
verified exact
local_arxiv, observed 2026-07-01T19:36:08.979591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-28T22:17:19.805524Z digest=sha256:f212f116c2d4c150a0b35a7762d6d5a46cef38f11f3bf053a89b9c6d538f2b5f

Observation 581395f8-b678-48c8-ad58-7c6527d39fb5 · outbound

This paper cites ET-BERT: A contextualized datagram representation with pre-training transformers for encrypted traffic classification.

A Protocol-Language Model for Network Intrusion (Without Deep Packet Inspection) ET-BERT: A contextualized datagram representation with pre-training transformers for encrypted traffic classification

Reference 4

Resolution
unresolved
no resolver link, observed 2026-06-28T22:17:19.805524Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-28T22:17:19.805524Z digest=sha256:a274be9d38bc9f69df627179b2f2234cca08ba88e157a3862b91159b399243eb

Observation 058e47d6-7047-49d0-8059-c2094e7a1c85 · outbound

This paper cites Intrusion detection using bidirectional LSTM recurrent neural network.

A Protocol-Language Model for Network Intrusion (Without Deep Packet Inspection) Intrusion detection using bidirectional LSTM recurrent neural network

Reference 5

Resolution
unresolved
no resolver link, observed 2026-06-28T22:17:19.805524Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-28T22:17:19.805524Z digest=sha256:78005fdc1d833762b0f18f3e5f306ad8e3bb2b20c2b0662b3d74f29071f49751

Observation 7f72f5fd-f285-4455-a983-cf35ff49418b · outbound

This paper cites Flow- bert: Learning network-flow representations for intrusion detection.

A Protocol-Language Model for Network Intrusion (Without Deep Packet Inspection) Flow- bert: Learning network-flow representations for intrusion detection

Reference 6

Resolution
unresolved
no resolver link, observed 2026-06-28T22:17:19.805524Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-28T22:17:19.805524Z digest=sha256:f5a711691c08847d35fd447c90671b15fc9b0454bd22bac67cfc9c24ea2be2f2

Observation 3acaef70-c943-412a-9c7c-ca878beb939d · outbound

This paper cites RWKV: Reinventing RNNs for the transformer era.

A Protocol-Language Model for Network Intrusion (Without Deep Packet Inspection) RWKV: Reinventing RNNs for the transformer era

Reference 7

Resolution
unresolved
no resolver link, observed 2026-06-28T22:17:19.805524Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-28T22:17:19.805524Z digest=sha256:dd0f176d7d476a947da339deaf292d5260e7fe02118a2229e3d8e12633db83a9

Observation 7e76e89d-307f-44eb-9412-6bc54e0badf0 · outbound

This paper cites Snort: Lightweight intrusion detection for networks.

A Protocol-Language Model for Network Intrusion (Without Deep Packet Inspection) Snort: Lightweight intrusion detection for networks

Reference 8

Resolution
unresolved
no resolver link, observed 2026-06-28T22:17:19.805524Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-28T22:17:19.805524Z digest=sha256:fb9cc230d7d059376898204cbb77f19bf1149e50a90129c88c1fa1d0864e0622

Observation fd7b3a73-3518-4c17-aad6-7685c5a0c11e · outbound

This paper cites Ghorbani.

A Protocol-Language Model for Network Intrusion (Without Deep Packet Inspection) Ghorbani

Reference 9

Resolution
unresolved
no resolver link, observed 2026-06-28T22:17:19.805524Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-28T22:17:19.805524Z digest=sha256:fe68872b340af5d6ad712b514341f1f8b836f0c54c9ae7a1841971dc57788c42

Observation 93ef8d0e-70a7-4c59-9284-026dececb932 · outbound

This paper cites Attention is all you need.

A Protocol-Language Model for Network Intrusion (Without Deep Packet Inspection) Attention is all you need

Reference 10

Resolution
unresolved
no resolver link, observed 2026-06-28T22:17:19.805524Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-28T22:17:19.805524Z digest=sha256:58fbaaa15265b2d0f3c916d028d35aaa6688f847fea69f3d4dcd545e062f6769

Observation 1a8443b3-c0ab-4268-a706-3007bded05bc · outbound

This paper cites Real Representations of $C_2$-Graded Groups: The Antilinear Theory.

A Protocol-Language Model for Network Intrusion (Without Deep Packet Inspection) Real Representations of $C_2$-Graded Groups: The Antilinear Theory

Reference 11

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T19:36:08.982368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-28T22:17:19.805524Z digest=sha256:dc8b014fc352547d285fdf3b674b43481079eb78c1a66978d800bb07c853c7d9

Observation b2da9f6f-4a4e-4e4c-b255-fced0095fbb9 · outbound

This paper cites End-to-end en- crypted traffic classification with one-dimensional convolution neural networks.

A Protocol-Language Model for Network Intrusion (Without Deep Packet Inspection) End-to-end en- crypted traffic classification with one-dimensional convolution neural networks

Reference 12

Resolution
unresolved
no resolver link, observed 2026-06-28T22:17:19.805524Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-28T22:17:19.805524Z digest=sha256:c1add58f91d1cf4bdb2b8271181e8ca41a85398dd39ada1a1333c1553111c43a

Pith citing papers

No inbound Pith citation observations are available.