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Paper Citation Record · LEDGER

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

As of 9 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 2026-08-09T06:31:02.800959+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

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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verified fuzzy
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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=2026-08-06T00:12:41.160900Z digest=sha256:13d1ea0ce9c2b9503d3982bd8db3d34a6c2f3aaec315bbee6e203ccd200c941e

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T00:12:41.252207Z digest=sha256:003714f9c7d3d21d5fed93b8438f204eb67076e0465980317d7fc7a76f5e0a48

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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raw_fallback, observed 2026-08-06T00:12:52.345366Z

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=2026-08-06T00:12:41.315830Z digest=sha256:82065c5a3a49232f609b845fa551a98b9204eb1d43276c9be925760a33c6c1f1

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

Resolution
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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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T00:12:41.358735Z digest=sha256:1714ce86501d4c2cf2f6b153a2f89807a4b853a84c7aff22ddd13656dd3a4e32

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

Resolution
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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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T00:12:41.460075Z digest=sha256:368561a47c33ab3541ad95b94e1bb7728b8dc46f4a613964f04e444b67c0eac4

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T00:12:41.529829Z digest=sha256:cd705b6790459fb3cd0aea3b3a8b042c864953be31d89da7d64def5664ebe6a7

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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raw_fallback, observed 2026-08-06T00:12:51.729272Z

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=2026-08-06T00:12:41.589431Z digest=sha256:b9a3aabd47d1fbafb9bbb0cc47db796da67b1e86e667a21d574d7ed88c3a7bd7

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T00:12:41.622204Z digest=sha256:fc783d941c05b5f23b8caec241891e2c63847c01e08a6c39c40dbba9e66be6b1

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T00:12:41.683413Z digest=sha256:ce97c5ebfb9f5d4d3712b348866d1eb17ee854cf33d70ddbafc1a977c412ced8

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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raw_fallback, observed 2026-08-06T00:12:51.395012Z

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=2026-08-06T00:12:41.768339Z digest=sha256:a3e2b42953653c1838c5bd59558062d73c80e85d158826012377c80a46c2f87e

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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unresolved
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=sha256:04edeac3fc2f4847dd9d2c8040f96d903b5e230c98a7f68313beff5aa9a5382d

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

Resolution
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=sha256:66b1f1c50caf5d097a65c81697312f13ee184d5b5af508d27b7f4d9766ba410a

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T00:12:41.962118Z digest=sha256:669a3b4a5d13d471ab910340b34ccad0b0810533bceef2863a4fab431eeb8c41

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T00:12:42.018467Z digest=sha256:3ec06f0573f31367975972722646de05f76ee8283b2b8e59d54018d5f729e9f0

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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raw_fallback, observed 2026-08-06T00:12:50.921794Z

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=2026-08-06T00:12:42.150437Z digest=sha256:76dd67e0913ff96fd02cbf4f056df4527c8895af18f9d8f50eae8e86de9e129a

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T00:12:42.190903Z digest=sha256:44ae20108a4e89cae6143e11657902664365a1c0ad29a5d18edea8751d34deaf

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=sha256:61e0472825b6f72f39e06f4b96674387e00e5ace31111d7cc6d93c356f43264c

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T00:12:42.261558Z digest=sha256:f33ae1843d953d785eb4444b3156d8e323e33f68a182b6ea5cf4d12d2c33bd4b

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T00:12:42.344739Z digest=sha256:761cf564d13aa551e4e89663258919c5f441259d5c5432a943b19607b55414b9

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=sha256:18d3f31e8de9c1e43439e5bd715ffe82bea2e096bb8f602422a2e35a60620f10

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

Resolution
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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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T00:12:42.458312Z digest=sha256:8d967338088f54e7fec7ee9c6cf68aadbc97a4a2c126230803c07d59663f4f97

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T00:12:42.557089Z digest=sha256:8cb7b877f933e2851b62e3c9e9f2d114796b60e8d158fa63f963727f6131fca6

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T00:12:42.606910Z digest=sha256:5670aed1fc53822d5a336d5ee8d9b6224b6cbac262f3594eb950a8e77ed900ad

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=sha256:2deeaded37eaf59e9d91607dc1ce2752387c7298a1ed2a59b2b7ca8df927fa15

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T00:12:42.830699Z digest=sha256:94125a95ea6a6a9d8df7c6e0ef6c09376b5f112f52f967feaa54372fc0d80d25

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T00:12:42.895706Z digest=sha256:2982847b8b34648a1973867cdc09503b383532afc81daeaeaebc63551147d01f

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=sha256:2a7c69b242ba7721c47f5172d12c314bfb46f89b0753b44e5f051152d283aaba

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T00:12:43.011954Z digest=sha256:7c7d0779a0216c60d977ef6c464393a230afa92091c31cd0f547d1844a7b34e7

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T00:12:43.109348Z digest=sha256:c86737241a967b9b96858b7bacdad09b3eab55a614d871827346098c6cc80abd

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T00:12:43.162226Z digest=sha256:f17fdbc2af365a1db4c24fb8e721041a2f8ed659e3e5f23c05b86a9bcc4925da

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=sha256:55b661e03cb72d4ea5d427b4af07b3ac873a14794a9c45ac670a018e976a2d52

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T00:12:43.288466Z digest=sha256:b6d4181432093000bab948de000090d50b7790beb6be31c0d11e13602f158b49

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T00:12:43.353304Z digest=sha256:3e082d85ed02d4a6f8e268fcde1854eba761429ce2dc7613bf995c3b2ac8b1d8

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T00:12:43.450297Z digest=sha256:7de7021da33458a1b5160f22fd6f98a65c6631b9f9018eeba96572d02e76fbe8

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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verified fuzzy
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T00:12:43.548591Z digest=sha256:39f22c6046775d6a9f1545413f0bd4803508f773e21f63ef7e230db9423cd103

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T00:12:43.623182Z digest=sha256:f58418b2ae647b9cd7e77959122b5bd8f065ab034a7d1ab313fefb544fdd3b13

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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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=sha256:39849f3e6e8121830a70993ea03c2612041b244da7e7bce705fea2c11dde9b19

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T00:12:43.756642Z digest=sha256:308f79f7940fda82a503a25628c45f3529f25736a4ade03e745d00fa30920c32

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T00:12:43.841500Z digest=sha256:36f20de2991ce0c0be3562490d95001d18a7ac8dc1b5889a7409eea50ce02799

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T00:12:43.943587Z digest=sha256:138c16f92d4a9cbc16bcdb1d9ec5c7d4e4a863441615cf8793ba107649b16fcf

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

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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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T00:12:44.070227Z digest=sha256:396ccd2191c507ccbd28d9b35ab96791e4db9bc293eb19daffe53cc1835f5224

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T00:12:44.145158Z digest=sha256:7c81736f5c2d0ce4bf2a4dd4b68fd875f070822890602433372e7a72680c6fca

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T00:12:44.217483Z digest=sha256:3b59688a70bddc805c2a631b82de157fbeb0d59b3f03329ceaf745edf6c1917f

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T00:12:44.322975Z digest=sha256:943a37cdfddf1f008d0e89f115f20a3f7f2cca2ee5294a43a3ad7c9b383712f6

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T00:12:44.400531Z digest=sha256:1b7b65034930dc72373cabf6c6c04317dfa5fe1b0c06fe2742096b56addc0ff7

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:c2c27aae66c66c9e2eba1d9eeb007ca968f9b4ba4bf248fbb6b6210a57554899

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

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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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T00:12:44.518711Z digest=sha256:72082045f6b86a860190a0614b7f99bebfe1fe0069ab07ec637c252e7daf66c8

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T00:12:44.600615Z digest=sha256:a1ebf9af47e1942f60537f15bdf0ba247ecc5fe73d78093364027f2102881cfe

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T00:12:44.687439Z digest=sha256:d5bbe136eb15e3ca2bee7377b78bf954f36288f8eb1f2ba2b351af0545dce4e7

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:dd1a7a4bf12b47cad4834b7ea2094a7b105aa7d486b2309c8611529d7c8042ae

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:ce2aa444d642f2c0eb3303995e091e5f42bf69cf39ac43060dc4c4dc9e9781fd

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T00:12:44.878240Z digest=sha256:529bd603429ad0936fd6a6623d712e27d50d8f32d929ed88c3f2d73703694b18

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T00:12:44.938287Z digest=sha256:622947084f257e5315e7b5076141833a421dc9820e6922dea5778e0ca3cd3f5f

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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unresolved
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=sha256:545e93f553e7e84c840a9c7d69415f4be9b914d0104d776143853a075785dd6a

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:e695e20298d445d50619f80bced9a546657c1d1a6997051ed26340f09bb8d2c0

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:f8aef5a22209e3d59d858351c3658a88056854b10e4a4a24c1dc7f63c9be0f40

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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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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T00:12:45.212720Z digest=sha256:a43cbc29c04415a5df34331850d01b234df58c17bbc39a91a9a56be081e35b75

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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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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T00:12:45.286712Z digest=sha256:9471b68dd4ce7976c4fede51c828d655277afcbcfe1bf91a21d5f0ba5fd19c22

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=sha256:185eb0440a8b7aa1d2d8497d22c8450795475c1278d8e7ddb52686826452fa22

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:c9284b05932a2973da2ef11a03855d48ef4319cd360a5bf3b30ae47bfb7c42c6

Pith citing papers

No inbound Pith citation observations are available.