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Paper Citation Record · LEDGER

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

As of 18 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 2026-08-18T06:34:40.430872+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=sha256:2a77a3b5a8a7a3f6a75d7f5247f557c1b0b532c15b0e41008ceac3d9d34274c6

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=sha256:3b3ab663aacba20c078c44c54bbea820c7b12897e9778f46fd58b4033d56959e

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-28T22:17:19.805524Z digest=sha256:f2fcf22e12e1102d7ce81fdd65c5ed316b55aed7f246003e8973474c97380359

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=sha256:10cd4731531e5f1f241ecf68378f332be3079b9dfbda5e2bc88677f8f0092f76

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:d7a9c431120106f9089dfcdc7d99b3103527252c6957465434cea8de75e853c8

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=sha256:666ae7918ded9a648c5211475c420530217c4c3d99a640f3ee883f63b0942998

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=sha256:614d4a55dffd91dff8f1efdea952e1947110f7f025662f2cf333ec082da6ee83

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=sha256:5df006d9db6dd5025fb1e65a78c1d703638bb1c0e14a1da80d027b0cff3e4825

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:f70b9fc587b8503bcee1f6213b480db8df570aa5dabeed935a88c3deeeaf8a14

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=sha256:2a90d846d506d54a5c3a68a23109e7f9dab0884a9c918d48a53a04e56042c0e5

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-28T22:17:19.805524Z digest=sha256:27aae22fd7df22ebc0d724700d71f5928deb4966f5f90f371ff9b24bafcd06f6

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:e77ff923abed39ed6f104ffa62e143b62189d08f391de522c9598597a2103b04

Pith citing papers

No inbound Pith citation observations are available.