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Paper Citation Record · LEDGER

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection

As of 15 August 2026, this Paper Citation Record lists 60 of 60 outbound references and 0 inbound Pith citation observations for arXiv:2608.01454.

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

pith.paper-citation-record.v1
2608.01454 v1

Coverage vector

measured 60 of 60 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T00:12:45.339878Z

measured 60 of 60 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+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

60 of 60 outbound references displayed

  • verified exact0
  • verified fuzzy43
  • unresolved16
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1b2534e7-e672-48d6-89e0-39727d96d701 · outbound

This paper cites Provenance-based in- trusion detection systems: A survey,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection Provenance-based in- trusion detection systems: A survey,

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 98c97d73-1d67-43dd-b241-c19105a18bb5 · outbound

This paper cites Are we there yet? an industrial viewpoint on provenance-based endpoint detection and response tools,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection Are we there yet? an industrial viewpoint on provenance-based endpoint detection and response tools,

Reference 2

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raw_fallback, observed 2026-08-06T00:12:52.490430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T00:12:41.252207Z digest=sha256:7b363d0f3d082683a336c1e8ef0446f6aeff529932db952c8525bb70d711d08e

Observation 014bc13f-f0b5-4875-9526-f2dd8b852303 · outbound

This paper cites SLEUTH: Real-time attack scenario reconstruction from COTS audit data,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection SLEUTH: Real-time attack scenario reconstruction from COTS audit data,

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T00:12:41.315830Z digest=sha256:39f5c7d267623606e4619777abb8bf407f5d158c4bd44a2dfd7363d42b0c3784

Observation 081d34ce-49d4-4d64-8413-551b679cffc5 · outbound

This paper cites HOLMES: Real-time APT detection through correlation of suspicious information flows,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection HOLMES: Real-time APT detection through correlation of suspicious information flows,

Reference 4

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raw_fallback, observed 2026-08-06T00:12:52.152844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T00:12:41.358735Z digest=sha256:bef8dcfbd1250975e917683c7e0d8ab1540b6daae17121f82194591d59352b8b

Observation b311dc26-245c-4469-84bb-8fb834565b0e · outbound

This paper cites Graph neural networks for intrusion detection: A survey,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection Graph neural networks for intrusion detection: A survey,

Reference 5

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raw_fallback, observed 2026-08-06T00:12:52.012334Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T00:12:41.460075Z digest=sha256:2c366fca20f5f9388bf876b20393e3fd562e04a7dd19993de9c229a6f622d23c

Observation 28c913c6-7489-46f3-9d79-8b430dbdfe45 · outbound

This paper cites KAIROS: Practical intrusion detection and investigation using whole- system provenance,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection KAIROS: Practical intrusion detection and investigation using whole- system provenance,

Reference 6

Resolution
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raw_fallback, observed 2026-08-06T00:12:51.852889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T00:12:41.529829Z digest=sha256:7a1a94ae056ef698614a199ff7d105c84f27d96b583d9ba4cd8186d9658afed6

Observation 57564db8-8b78-48af-9613-782fb9a0d7de · outbound

This paper cites THREATRACE: Detecting and tracing host-based threats in node level through provenance graph learning,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection THREATRACE: Detecting and tracing host-based threats in node level through provenance graph learning,

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T00:12:41.589431Z digest=sha256:6aa33e1a5a9869bbc9ec392612887f6b05480c1eaa449bebeee5cfb5152c8f94

Observation bfc4c7c5-d544-4ff6-886c-3f5ffdf1643f · outbound

This paper cites On the reproducibility of provenance-based intrusion detection that uses deep learning,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection On the reproducibility of provenance-based intrusion detection that uses deep learning,

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T00:12:41.622204Z digest=sha256:5d8b02d26d91678f22d1029dfacef2be84b9029cb6add9f0245a221de970db2f

Observation d583f4ce-ffed-4405-87ed-a29a8c0955f7 · outbound

This paper cites Sometimes simpler is better: A comprehensive analysis of state-of-the-art provenance-based intrusion detection systems,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection Sometimes simpler is better: A comprehensive analysis of state-of-the-art provenance-based intrusion detection systems,

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T00:12:41.683413Z digest=sha256:495491b32b6895014d704fd7b05a1617db4fd4f8ca903982613aab394fd2fea7

Observation ffa7a138-40ae-4934-b34d-aae264bdb4fe · outbound

This paper cites What we talk about when we talk about logs: Understanding the effects of dataset quality on endpoint threat detection research,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection What we talk about when we talk about logs: Understanding the effects of dataset quality on endpoint threat detection research,

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T00:12:41.768339Z digest=sha256:e8018434b211d11d9135f1c4c1369b255310a6eab23051c6c9afd480451c5487

Observation 68a231a9-cf9c-4a5c-840e-8881cf72fbdb · outbound

This paper cites On the forensic validity of approximated audit logs,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection On the forensic validity of approximated audit logs,

Reference 11

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no resolver link, observed 2026-08-06T00:12:41.816860Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T00:12:41.816860Z digest=sha256:065383ed641ad993ba59a6d9241537df33767f96c9472f907ae09752ffe7e171

Observation 31df0c72-4f68-4d0e-b267-369010e1d746 · outbound

This paper cites Shortcut learning in deep neural networks,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection Shortcut learning in deep neural networks,

Reference 12

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unresolved
no resolver link, observed 2026-08-06T00:12:41.908831Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T00:12:41.908831Z digest=sha256:5afe1e249f81fd6fd249b6369592d9c80cc84e28d6cea7e4ff7c779c08e35693

Observation 398fe4c0-2b44-4991-aafe-276d73b4720e · outbound

This paper cites ORTHRUS: Achieving high quality of attribution in provenance-based intrusion detection systems,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection ORTHRUS: Achieving high quality of attribution in provenance-based intrusion detection systems,

Reference 13

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raw_fallback, observed 2026-08-06T00:12:51.201616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T00:12:41.962118Z digest=sha256:46878ed04fa7199ca91bd45bd0c441d17f43a98c28a49acf3aff0b17865d2c89

Observation a66f594c-388c-4de3-9a74-e21cd1251432 · outbound

This paper cites NoDoze: Combatting threat alert fatigue with automated provenance triage,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection NoDoze: Combatting threat alert fatigue with automated provenance triage,

Reference 14

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raw_fallback, observed 2026-08-06T00:12:51.060852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T00:12:42.018467Z digest=sha256:f7885e9ef5e66810eef0b4aece5908c914524abada9343ced1f7ccacb3ee64c7

Observation 19e194f4-3f25-4c0e-88c3-7a1c44a28dbe · outbound

This paper cites Back-Propagating system dependency impact for attack investigation,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection Back-Propagating system dependency impact for attack investigation,

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T00:12:42.150437Z digest=sha256:2939552007f24e857f3dedc8e5ccec7d4e50f23b620e1b4551bc27aa069825d7

Observation 309684a1-d780-40a6-ac80-03f61b054ede · outbound

This paper cites NODLINK: An online system for fine-grained apt attack detection and investigation,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection NODLINK: An online system for fine-grained apt attack detection and investigation,

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T00:12:42.190903Z digest=sha256:539ba2185d86d4434327516c486101caccc12681275e87f5a033fe516ffdacda

Observation fa5112cd-33b8-4f85-88ea-0ce5ab7a2755 · outbound

This paper cites Dos and don’ts of machine learning in computer security,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection Dos and don’ts of machine learning in computer security,

Reference 17

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no resolver link, observed 2026-08-06T00:12:42.219769Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T00:12:42.219769Z digest=sha256:9ee249a569ff36838f1aa69a2651a342b5b7242c42e23764403387f45dc44960

Observation b6e70a15-8dca-4536-bc71-b82b5e68ea24 · outbound

This paper cites Transparent computing engagement 3 data release,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection Transparent computing engagement 3 data release,

Reference 18

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raw_fallback, observed 2026-08-06T00:12:50.587011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T00:12:42.261558Z digest=sha256:473b09ca308e9c5d3618eb44574bea93588f8220985da59dd03f97cb1c2dedca

Observation 384d63fe-4220-43c8-b976-5998713fafec · outbound

This paper cites REAPr: Recovery every attack process,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection REAPr: Recovery every attack process,

Reference 19

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raw_fallback, observed 2026-08-06T00:12:50.474000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T00:12:42.344739Z digest=sha256:dda13e03555163522807527712bcb4a87a20f5f725fe1c54a11c04de93eb4396

Observation 8082b64b-40cc-4ee0-a338-61ed37012353 · outbound

This paper cites ATLASv2: ATLAS Attack Engagements, Version 2.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection ATLASv2: ATLAS Attack Engagements, Version 2

Reference 20

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no resolver link, observed 2026-08-06T00:12:42.400804Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T00:12:42.400804Z digest=sha256:bf8496f6f20f0a0e9cbe8d736568d4e98bdce528ee971bd48a8f0836b63fa4f3

Observation ba49a220-ad07-4dbd-89e8-7423264bf2a5 · outbound

This paper cites How to effectively trace provenance on windows endpoint detection & response telemetry,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection How to effectively trace provenance on windows endpoint detection & response telemetry,

Reference 21

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raw_fallback, observed 2026-08-06T00:12:50.244315Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T00:12:42.458312Z digest=sha256:396b3ab5cae55e92b951268d112c933df2528494f7c1d279196f2dfe03f9149c

Observation 4d9d56f6-bbcf-4e75-a50d-342b5b4e04e7 · outbound

This paper cites SPADE: Support for provenance auditing in distributed environments,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection SPADE: Support for provenance auditing in distributed environments,

Reference 22

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raw_fallback, observed 2026-08-06T00:12:50.075333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T00:12:42.557089Z digest=sha256:276debed6750484423e2b8569340cc9eeebf6697a58e6c4ea50646346ed0c8a3

Observation 078e3ad3-9a76-42cc-ba7f-27878d15cde8 · outbound

This paper cites Practical whole-system provenance capture,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection Practical whole-system provenance capture,

Reference 23

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raw_fallback, observed 2026-08-06T00:12:49.887090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T00:12:42.606910Z digest=sha256:09d3b152df207baf673300db8ab9114a17a79db5de8adc090d7c2e118ec75b66

Observation 1c389a06-d7c4-4039-9d82-197e15daa6d7 · outbound

This paper cites Trustworthy Whole- System provenance for the linux kernel,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection Trustworthy Whole- System provenance for the linux kernel,

Reference 24

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unresolved
no resolver link, observed 2026-08-06T00:12:42.724756Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T00:12:42.724756Z digest=sha256:1dd168b7f6137b438e5870e90a12f52c30f2b79be6e991582020b209bd2a6f53

Observation 6e5af8c3-4017-4041-8be1-eafd7dc0a266 · outbound

This paper cites Loggc: garbage collecting audit log,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection Loggc: garbage collecting audit log,

Reference 25

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raw_fallback, observed 2026-08-06T00:12:49.714635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T00:12:42.830699Z digest=sha256:42be5b4cad7b0ac8c1192cd3d474b98003440dcb8859d9ae39a0138e818ca6e7

Observation 5a2182e3-c245-4834-8eef-f96bde56f6a8 · outbound

This paper cites High accuracy attack provenance via binary-based execution partition,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection High accuracy attack provenance via binary-based execution partition,

Reference 26

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raw_fallback, observed 2026-08-06T00:12:49.523997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T00:12:42.895706Z digest=sha256:006850b9bc8c596ccefb81a06399333b95ca081641dc4a05f7e85a1cd8448ce3

Observation 49df516c-23f0-4e9d-b3c9-c95197c068d2 · outbound

This paper cites High fidelity data reduction for big data security dependency analyses,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection High fidelity data reduction for big data security dependency analyses,

Reference 27

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no resolver link, observed 2026-08-06T00:12:42.961980Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T00:12:42.961980Z digest=sha256:2cf781cae009e1276c2aba7c3b91a2ec27f15a6e27121a695e10558dc6424160

Observation fa2f49b0-76b1-45e6-804e-a6b1c0886d99 · outbound

This paper cites Towards a timely causality analysis for enterprise security,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection Towards a timely causality analysis for enterprise security,

Reference 28

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raw_fallback, observed 2026-08-06T00:12:49.364034Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T00:12:43.011954Z digest=sha256:c82944e39e0e2047d481c07a76fd45a65d0287a371f228dbd66f42ef41d6e5e9

Observation 8864fcf1-f417-4aea-ba39-fce16ae2497d · outbound

This paper cites W ATSON: Abstracting behaviors from audit logs via aggregation of contextual semantics,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection W ATSON: Abstracting behaviors from audit logs via aggregation of contextual semantics,

Reference 29

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raw_fallback, observed 2026-08-06T00:12:49.247072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T00:12:43.109348Z digest=sha256:ed2c03a7b19022a1e581bcd960c08909756264a0efc6307f43ca5ec39c170072

Observation 2c8da824-15bc-41a8-8fdd-d3e75db6057b · outbound

This paper cites DeepLog: Anomaly detection and diagnosis from system logs through deep learning,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection DeepLog: Anomaly detection and diagnosis from system logs through deep learning,

Reference 30

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raw_fallback, observed 2026-08-06T00:12:49.138030Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T00:12:43.162226Z digest=sha256:243516acb502694cebdfa5bb9878a5fd18d2f921df9759e6737123f097146bf1

Observation ca22fd31-f60c-4a52-8ee3-b7daa313a44d · outbound

This paper cites Logbert: Log anomaly detection via bert,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection Logbert: Log anomaly detection via bert,

Reference 31

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no resolver link, observed 2026-08-06T00:12:43.236308Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T00:12:43.236308Z digest=sha256:eba82010bf6bc3134bdf637e6df89949f58fbd635dfb7646db7e2fd25a3c2642

Observation 817068f6-d3c9-4b24-9c84-8fbf1f897b22 · outbound

This paper cites Unicorn: Runtime provenance-based detector for advanced persistent threats,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection Unicorn: Runtime provenance-based detector for advanced persistent threats,

Reference 32

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raw_fallback, observed 2026-08-06T00:12:49.022650Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T00:12:43.288466Z digest=sha256:9488bc2fcc8d18f326349e78e6b885596a0ba617e759eb4f46bfc499ae159ab8

Observation cbb42c45-b1e5-4c75-969d-bb37a4bf647e · outbound

This paper cites You are what you do: Hunting stealthy malware via data provenance analysis,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection You are what you do: Hunting stealthy malware via data provenance analysis,

Reference 33

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raw_fallback, observed 2026-08-06T00:12:48.902383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T00:12:43.353304Z digest=sha256:b09a34ffb585f94a1171bea4339946fad2ad7be6de665a637402c99bcc69d667

Observation c347928f-6746-4ebb-8f42-dcb10f5e98e9 · outbound

This paper cites MAGIC: Detecting advanced persistent threats via masked graph representation learning,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection MAGIC: Detecting advanced persistent threats via masked graph representation learning,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:12:48.736900Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T00:12:43.450297Z digest=sha256:f443b8dccd845b01fc6d61adf8993975f14e7f679ce975ee4282d1809da61eba

Observation d9de7929-3d37-499f-ad09-65429f726d7e · outbound

This paper cites Flash: A comprehensive approach to intrusion detection via provenance graph representation learning,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection Flash: A comprehensive approach to intrusion detection via provenance graph representation learning,

Reference 35

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raw_fallback, observed 2026-08-06T00:12:48.530584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T00:12:43.548591Z digest=sha256:66a2852403b43511cc5bf82c3b35046075d2d92e5717d560fc6b6da3fe486ae3

Observation 518464f2-9bf4-4cc5-950e-8ad3fe6978be · outbound

This paper cites R-caid: Embedding root cause analysis within provenance-based intrusion detection,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection R-caid: Embedding root cause analysis within provenance-based intrusion detection,

Reference 36

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verified fuzzy
raw_fallback, observed 2026-08-06T00:12:48.328184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T00:12:43.623182Z digest=sha256:1030c88fcd11b423b4f5d5720bd60492d1bb473cf81df3cbfee3a799181d4110

Observation a660ef32-ceeb-4133-962d-4f96970811de · outbound

This paper cites The relationship between precision-recall and roc curves,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection The relationship between precision-recall and roc curves,

Reference 37

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unresolved
no resolver link, observed 2026-08-06T00:12:43.689445Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T00:12:43.689445Z digest=sha256:df755ec279bc721d995b09f3a4c3d2187012887a0444f3a3961c02a274eb1fe6

Observation 878e8b01-7f42-4ddd-9746-a07b099e58fa · outbound

This paper cites The precision-recall plot is more informa- tive than the ROC plot when evaluating binary classifiers on imbalanced datasets,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection The precision-recall plot is more informa- tive than the ROC plot when evaluating binary classifiers on imbalanced datasets,

Reference 38

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verified fuzzy
raw_fallback, observed 2026-08-06T00:12:48.133903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T00:12:43.756642Z digest=sha256:72e8e0a137c7d3ca00b1eb29f67124abdf1832b07c056230689894041b8e6906

Observation eac5dabe-bbc9-43b9-a83b-f70be375ea83 · outbound

This paper cites The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:12:47.912820Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T00:12:43.841500Z digest=sha256:b0691bf78694f6e00ea7c0a00ae52de16e954d7818f96fc491ee1dbf5220f5d1

Observation 9c6f43c3-6e4c-471b-8fb4-4836901aa0cf · outbound

This paper cites TESSERACT: Eliminating experimental bias in malware classification across space and time (extended version),.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection TESSERACT: Eliminating experimental bias in malware classification across space and time (extended version),

Reference 40

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verified fuzzy
raw_fallback, observed 2026-08-06T00:12:47.671281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T00:12:43.943587Z digest=sha256:0a4b8ff6177aff9d20e71fda7fce83d4c6a37cbbb0d17c9ba9bdbd049b671a0d

Observation 5fcbca1c-a2d7-4a27-8582-b33706da386b · outbound

This paper cites SoK: Pragmatic assessment of machine learning for network intrusion detection,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection SoK: Pragmatic assessment of machine learning for network intrusion detection,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:12:47.488415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T00:12:44.070227Z digest=sha256:36e45b90831a624ccd142cf0092fcbe1f0445ce33a45c15176d6d90d533297f9

Observation ce8503cc-bd4d-4196-8fc8-cda7aa5c144a · outbound

This paper cites Reporting score distributions makes a difference: Performance study of lstm-networks for sequence tagging,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection Reporting score distributions makes a difference: Performance study of lstm-networks for sequence tagging,

Reference 42

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verified fuzzy
raw_fallback, observed 2026-08-06T00:12:47.372132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T00:12:44.145158Z digest=sha256:80293e9a53bcd0aed59f0ed523993454c26c1848cd835ab9c92e0540d6a95187

Observation d797dbc1-fe65-44e4-aa57-8ae18cb42e19 · outbound

This paper cites Accounting for variance in machine learning benchmarks,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection Accounting for variance in machine learning benchmarks,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:12:47.271093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T00:12:44.217483Z digest=sha256:0fbe4fd42201d3bbfd7ea36d75bb4e406bfbfba19f44b3727f59febd6f392705

Observation 30d1f2f5-e5b3-407c-b2ac-3aa28af46cf6 · outbound

This paper cites ATLAS: A sequence-based learning approach for attack investigation,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection ATLAS: A sequence-based learning approach for attack investigation,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:12:47.122348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T00:12:44.322975Z digest=sha256:deead36e31f030e7687f5871fc829765cc88ada008cf2d362dd3dbb4424b7e21

Observation a5724c73-9983-40bb-bfb8-77df8c70a2d6 · outbound

This paper cites A new hope for darpa optc,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection A new hope for darpa optc,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:12:47.023073Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T00:12:44.400531Z digest=sha256:31bc62761f3de79a94ae1efab50934219c1df4e625f8a079210ca3cdbc1bb9c0

Observation cdae3c81-148e-4413-adc2-213d4c701500 · outbound

This paper cites A mathematical theory of communication,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection A mathematical theory of communication,

Reference 46

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unresolved
no resolver link, observed 2026-08-06T00:12:44.459624Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T00:12:44.459624Z digest=sha256:a88d9f75ba31ba1d95d817cd005fe14ae11eb1e1291c8e05ddab82d69fa25453

Observation d41d2e39-d3ca-40b5-b797-9f851fe0009a · outbound

This paper cites Survivalism: Systematic analysis of Windows malware living- off-the-land,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection Survivalism: Systematic analysis of Windows malware living- off-the-land,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:12:46.913789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T00:12:44.518711Z digest=sha256:ea42b5d622e914f31c99a4d6e6cc70c361b41bf1145aef216351729136e2387d

Observation cc61a368-ea8c-416f-a613-4d0a5e386c39 · outbound

This paper cites Self-supervised learning of graph representations for network intrusion detection,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection Self-supervised learning of graph representations for network intrusion detection,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:12:46.747486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T00:12:44.600615Z digest=sha256:8bc4099b083285cd1e34b2dc56a0aedb5fb9124debd4f4d1e755b44b377d63ea

Observation 7fab8737-07e1-4e1b-a694-82727c9141be · outbound

This paper cites E- GraphSAGE: A graph neural network based intrusion detection system for IoT,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection E- GraphSAGE: A graph neural network based intrusion detection system for IoT,

Reference 49

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verified fuzzy
raw_fallback, observed 2026-08-06T00:12:46.594080Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T00:12:44.687439Z digest=sha256:a7a6d719ed23cb19701478af1e0d951ca388eef3e3ad9648945e614c998491fc

Observation 39fae256-bedb-426e-b059-148129e59ebb · outbound

This paper cites Attention is all you need,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection Attention is all you need,

Reference 50

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unresolved
no resolver link, observed 2026-08-06T00:12:44.758185Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T00:12:44.758185Z digest=sha256:9e18155703585beb8d92f4694557c99bb7fcde3579a8ac4f8fae8ea6cc9e6249

Observation 465093ae-7a6d-4c2c-b48b-4b7642618196 · outbound

This paper cites Efficient Estimation of Word Representations in Vector Space.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection Efficient Estimation of Word Representations in Vector Space

Reference 51

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unresolved
no resolver link, observed 2026-08-06T00:12:44.815942Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T00:12:44.815942Z digest=sha256:c3e1bbd31bccc6cdc7287c509fc91d2658a388c51d968e54fbf7f4e0560a9e76

Observation 517f5e5f-8ea7-44f5-b810-f0a53eca5e9e · outbound

This paper cites PIDSMaker: An ml framework for building provenance- based intrusion detection systems,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection PIDSMaker: An ml framework for building provenance- based intrusion detection systems,

Reference 52

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verified fuzzy
raw_fallback, observed 2026-08-06T00:12:46.454123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T00:12:44.878240Z digest=sha256:72c102da7113cd7d2f620b1eea517d334b9a5992c6aa82869157b6a7a75c10ee

Observation c6ff909b-ad66-4dd9-b3f1-1b4b23daa5d2 · outbound

This paper cites MAGIC: Official implementation,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection MAGIC: Official implementation,

Reference 53

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verified fuzzy
raw_fallback, observed 2026-08-06T00:12:46.340069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T00:12:44.938287Z digest=sha256:fd23b7d02a4d17a38a7db76e5c75a5fae4fdeb183a674c0e763a0ff033f2929b

Observation c5d7783f-995e-4c65-94fc-d4a6b16c7930 · outbound

This paper cites PyTorch: An imperative style, high-performance deep learning library,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection PyTorch: An imperative style, high-performance deep learning library,

Reference 54

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no resolver link, observed 2026-08-06T00:12:44.998573Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T00:12:44.998573Z digest=sha256:c2eb24f248ae98d59097ce9c5f8ee1036606f80ba8a65168f6faff317f371f4a

Observation 7acf3fce-6595-4174-b44a-f44838b9ed54 · outbound

This paper cites Fast Graph Representation Learning with PyTorch Geometric.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection Fast Graph Representation Learning with PyTorch Geometric

Reference 55

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unresolved
no resolver link, observed 2026-08-06T00:12:45.066398Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T00:12:45.066398Z digest=sha256:65a296470f583afdd282165c041613b841a6227c385c8565e4ceda13cce8b654

Observation e0fe0935-6403-45dc-b53e-2e69506286a3 · outbound

This paper cites Decoupled weight decay regularization,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection Decoupled weight decay regularization,

Reference 56

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no resolver link, observed 2026-08-06T00:12:45.133827Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T00:12:45.133827Z digest=sha256:8ecb0bce466d4d8215480df8049c570ef39ba8c9b8ef07239e7c3007ea037233

Observation e814970b-1a85-4f59-ad7e-52324320c762 · outbound

This paper cites Datasheets for datasets,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection Datasheets for datasets,

Reference 57

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verified fuzzy
raw_fallback, observed 2026-08-06T00:12:46.207367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T00:12:45.212720Z digest=sha256:3ae5aabd62c5f3a0e7e2c95c0574c851b7bf01cb166146c7935f5f779c1fc0b3

Observation 7712aa8d-b2a5-43fc-af26-6b98f82b9b88 · outbound

This paper cites The Menlo Report: Ethical principles guiding information and communication technology research,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection The Menlo Report: Ethical principles guiding information and communication technology research,

Reference 58

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verified fuzzy
raw_fallback, observed 2026-08-06T00:12:46.080576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T00:12:45.286712Z digest=sha256:528bce6c66abe03369bfbf7c21a38dc97ce19dc4e6fdfe522d20769e9a94753d

Observation c8fc40f3-198a-4837-82cd-d7d1048d2491 · outbound

This paper cites Fast memory-efficient anomaly detection in streaming heterogeneous graphs,.

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection Fast memory-efficient anomaly detection in streaming heterogeneous graphs,

Reference 59

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unresolved
no resolver link, observed 2026-08-06T00:12:45.339878Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T00:12:45.339878Z digest=sha256:5359055cf2575ae25688fb703a2edd9ae8c5ae918bf356d2575b4047faf86819

Observation 682bef6d-5863-4aa0-bdcd-db50a4b18a78 · outbound

This paper cites TESSERACT: Eliminating Experimental Bias in Malware Classification across Space and Time (Extended Version).

How Benchmarks and Evaluation Protocols Shape Conclusions in Provenance-Based Intrusion Detection TESSERACT: Eliminating Experimental Bias in Malware Classification across Space and Time (Extended Version)

Reference 2025

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no resolver link, observed 2026-08-06T00:12:44.013859Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T00:12:44.013859Z digest=sha256:9d05fad814bbb97b502031a36ab0af84ea3347e248c5b64f2ab7b0872c98f00d

Pith citing papers

No inbound Pith citation observations are available.