Paper Citation Record · LEDGER

APT-LLM: Embedding-Based Anomaly Detection of Cyber Advanced Persistent Threats Using Large Language Models

As of 9 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 0 inbound Pith citation observations for arXiv:2502.09385.

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

pith.paper-citation-record.v1
2502.09385 v1

Coverage vector

measured 12 of 12 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T21:44:03.982650Z

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 exact0
verified fuzzy10
unresolved2
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2775465d-1985-4e8f-9bfa-a89d6290ec91 · outbound

This paper cites Strategically-motivated advanced persistent threat: Definition, process, tactics and a disinformation model of coun- terattack,.

APT-LLM: Embedding-Based Anomaly Detection of Cyber Advanced Persistent Threats Using Large Language Models Strategically-motivated advanced persistent threat: Definition, process, tactics and a disinformation model of coun- terattack,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:44:04.091945Z

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.

Observation 65873729-e507-4f93-8bec-5a3ebde0fd45 · outbound

This paper cites A systematic literature review on advanced persistent threat behaviors and its detection strategy,.

APT-LLM: Embedding-Based Anomaly Detection of Cyber Advanced Persistent Threats Using Large Language Models A systematic literature review on advanced persistent threat behaviors and its detection strategy,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:44:04.083545Z

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.

Observation aa2e16b2-0c4e-4fbe-9a2d-d07db58ac8b9 · outbound

This paper cites A survey on evaluation of large language models,.

APT-LLM: Embedding-Based Anomaly Detection of Cyber Advanced Persistent Threats Using Large Language Models A survey on evaluation of large language models,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T21:44:03.953133Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 345d1aec-2a6f-40e2-8300-4858a48b9913 · outbound

This paper cites Large Language Models in Cybersecurity: State-of-the-Art.

APT-LLM: Embedding-Based Anomaly Detection of Cyber Advanced Persistent Threats Using Large Language Models Large Language Models in Cybersecurity: State-of-the-Art

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T21:44:03.956555Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 675ee37c-4e7c-4cc4-ba22-e11100616c44 · outbound

This paper cites A scalable and efficient outlier detection strategy for categorical data,.

APT-LLM: Embedding-Based Anomaly Detection of Cyber Advanced Persistent Threats Using Large Language Models A scalable and efficient outlier detection strategy for categorical data,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:44:04.070578Z

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.

Observation 57e2fb60-1b44-4a22-bcd5-d13cfe67b89b · outbound

This paper cites The odd one out: Identifying and char- acterising anomalies,.

APT-LLM: Embedding-Based Anomaly Detection of Cyber Advanced Persistent Threats Using Large Language Models The odd one out: Identifying and char- acterising anomalies,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:44:04.063610Z

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.

Observation c33c07af-37b3-4a0f-acd0-27f989d3cc11 · outbound

This paper cites Outlier detection for transaction databases using association rules,.

APT-LLM: Embedding-Based Anomaly Detection of Cyber Advanced Persistent Threats Using Large Language Models Outlier detection for transaction databases using association rules,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:44:04.057036Z

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.

Observation 2de9c4e7-b15f-41ed-82c3-98c7c9148a2d · outbound

This paper cites A baseline for unsupervised advanced persistent threat detection in system-level provenance,.

APT-LLM: Embedding-Based Anomaly Detection of Cyber Advanced Persistent Threats Using Large Language Models A baseline for unsupervised advanced persistent threat detection in system-level provenance,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:44:04.049652Z

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.

Observation 6befc9b3-7b9e-4715-83fb-ef03d2be19dd · outbound

This paper cites A rule mining-based advanced persistent threats detection system,.

APT-LLM: Embedding-Based Anomaly Detection of Cyber Advanced Persistent Threats Using Large Language Models A rule mining-based advanced persistent threats detection system,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:44:04.040118Z

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.

Observation 20d2946e-9b08-40e9-9a1e-ab90f4e57bfd · outbound

This paper cites Hack me if you can: Aggregating autoencoders for countering persistent access threats within highly imbalanced data,.

APT-LLM: Embedding-Based Anomaly Detection of Cyber Advanced Persistent Threats Using Large Language Models Hack me if you can: Aggregating autoencoders for countering persistent access threats within highly imbalanced data,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:44:04.031930Z

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.

Observation 30b4e05e-6547-4488-905c-a72349ac2581 · outbound

This paper cites A survey of large language models for cyber threat detection,.

APT-LLM: Embedding-Based Anomaly Detection of Cyber Advanced Persistent Threats Using Large Language Models A survey of large language models for cyber threat detection,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:44:04.022110Z

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.

Observation d1ab48f8-65a2-4175-9fec-8f21b8b85e47 · outbound

This paper cites Cysecbert: A domain-adapted language model for the cybersecurity domain,.

APT-LLM: Embedding-Based Anomaly Detection of Cyber Advanced Persistent Threats Using Large Language Models Cysecbert: A domain-adapted language model for the cybersecurity domain,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:44:04.011803Z

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.

Pith citing papers

No inbound Pith citation observations are available.