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Paper Citation Record · LEDGER

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

As of 13 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 2026-08-13T06:32:02.005865+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 2026-08-13T06:32:02.005865+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 2026-08-13T06:32:02.005865+00:00.

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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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T00:12:41.315830Z digest=sha256:f51348a25525d681b39400182a376bbcc42db420e58017208ba69c589a46dec8

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T00:12:41.358735Z digest=sha256:9ed49f58cb29e0ca437f7469a82610407004f379f57e17e0ab16d497d2e02a61

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T00:12:41.460075Z digest=sha256:94370835cb257c4effea14b50b408ed7a914fbfcc678d19956c7377ec78a38c2

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T00:12:41.529829Z digest=sha256:31b3b3d8356aafbd997babd1744901f89a0cc0329af7d919f6a1d7d6c4db584d

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T00:12:41.589431Z digest=sha256:79e517b8e152b84133224a9d82e00419794b9119150e81a23dbd58c052db6a47

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T00:12:41.622204Z digest=sha256:2f9fb939c629420ce8acee2dacfba8e376e1c6630a97a16a69ab7d2c7a0a2cdc

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T00:12:41.683413Z digest=sha256:ec8196199f2ccab117803fb8cd1766251c36064b72623083b4621c218aae4b5c

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T00:12:41.768339Z digest=sha256:8c65ad47393a880110a4a91b6a4ba121868055999802da5dcb9dc9a59fde8b43

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=sha256:68ba4ade8b0a508ee6c34433ec0456fadba661fe543c3948470fe11ea374bfbf

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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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:f5779641ebc08e4f949f477a005e84dbbba316886d27a58e371a3909313c97d1

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T00:12:41.962118Z digest=sha256:1bea0bc402d114c1c75675ac87aeaab16866f2bd69f36d3fe8748c9779e458c7

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T00:12:42.018467Z digest=sha256:b03c9977999b3f0a5f9ca2f9656286acd6061295d028038718e07be0faa6f1bd

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T00:12:42.150437Z digest=sha256:5c3154e7e6acf36346bfe1068a918341dee5f25ae27943a12168d6c3a0cd25a4

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T00:12:42.190903Z digest=sha256:40e0560f65383edeede9ed7b02c25fe9b2ce5b36a7802a357102d9d52fda01ba

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:f2e68a9bc41b7b1f55b0bd1609667c960cfea61ef8f4f999d4a6981f7300fd72

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T00:12:42.261558Z digest=sha256:b468e3e95646fd61f5340ad7f9346bdfd5dd20267a3d89fc2638146d5fc20146

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T00:12:42.344739Z digest=sha256:1f511c7d8c54e6e30b333417d631931a05f8cff2f07ac2f1c651b78104530bc0

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:fd3524eb64e35fdc61ce5f6fc06ed351e4c296cef9391334987438a82407298e

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T00:12:42.458312Z digest=sha256:959cfdfa89e1fafcf58b2151e802fe4afe5c1d1aabb8d6ff45ce95d7395b08d7

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T00:12:42.557089Z digest=sha256:805febeba01625ccba91b112884a4923fac029a775936309ffb1b4ad7177a180

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T00:12:42.606910Z digest=sha256:aadaab065d0d3c4b1ee28f03e19d5901989ede04a4c02adae963b17b923e0208

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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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=sha256:06562746e06b10df8bad895f886a25767e8a67999c274c28e7f7863b806a1e08

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T00:12:42.830699Z digest=sha256:b6595badace4b9c945ecbf7652bdf33c9bdbc2bd83afcd0ae817da599d877fbd

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T00:12:42.895706Z digest=sha256:7bb94bac734842f2e9c92e0cff3a88e97969316e0f9572e2f49f2ce0430e32af

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:aab459941e93ac7274a3ce1a2f488c0ea12c6c80eb7553e8d86f9829bf008270

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T00:12:43.011954Z digest=sha256:f0a133811cf9f3775a62913bccf2829c6eb7c4fa013ccd2b80dfd6cadb4f6957

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T00:12:43.109348Z digest=sha256:3f62d9e661aa2aec5773e64eef67a93a57d39d277ad36cc7da6e8bb6bf49d3b0

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T00:12:43.162226Z digest=sha256:7b30ff9b3087e4d4e9ab9dadce95fc24f75f42f88099d915b03ab6c3239ef263

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=sha256:705ff2b580f5d2a4ac4c9fe13ca8d27baf6125cc32504dadd3665e59f6378ade

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T00:12:43.288466Z digest=sha256:bd775816a8030e124af1df0249829635600cd125db5d78547ae4093db44151e5

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T00:12:43.353304Z digest=sha256:6cfdd6762d68c3351eb352512538bdf67c300791dbaaaa85dde494f6f07058c0

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T00:12:43.450297Z digest=sha256:ec674e627356ca07ddbd06140d6d2a9889664c820286b211ab83c8f4ac962956

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T00:12:43.548591Z digest=sha256:08ad0eb41161e41754e047337b7918b904d2a00d600f9890cade03cd3dfbc347

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T00:12:43.623182Z digest=sha256:499ca38d41deb2e3a8c2b6464e35569f015afd118b7c57b2e5aadb00be2a9f18

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:d27719d5bb0e022aef0a1ed0f09a6de5efe063c5fa78496b89dcadfcb34a9dab

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T00:12:43.756642Z digest=sha256:50d9f7a146bc1eebaad4947fada5ff005871fc964a818fef4b25a875e344e518

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T00:12:43.841500Z digest=sha256:c65b11ef190fe20df80edeb83bb79801fac214faaa70763e6f1e53d3e31a8557

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T00:12:43.943587Z digest=sha256:d4ebdd2f9be501707fe611240c1e0b88ab3a7a2fb3f42226465996e543d5722d

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T00:12:44.070227Z digest=sha256:50856a6a6d82d8be1cb9b3cf4bbe8a6c7921fcc5115fea4d268a48851a575d1d

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

Resolution
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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T00:12:44.145158Z digest=sha256:a4db785c2d622a6459489be7836a8baa89033ab21443c19a8942976f1e28eb0a

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T00:12:44.217483Z digest=sha256:2b0b901390d592a1a4b4aebf41301e42bdd64040385f437d4c802701101b859d

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T00:12:44.322975Z digest=sha256:0e6257e2bd8473f1cf1d755953c6eb11dfcc63e79bec0a43342b333c0ca8177f

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T00:12:44.400531Z digest=sha256:9ae273364360657b173826dc6e7689876e9c7b93079c0c6fb074fb83d0016798

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=sha256:27b32cc2f3cf73f2a2e32dc51c99a5090ded1a9672c36be0d43d3333f8caa97c

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T00:12:44.518711Z digest=sha256:654da0ef35920415aaa79ead36ec775e051a558c7973726a7e5decad01d4d521

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T00:12:44.600615Z digest=sha256:072732b28a3fa5a9a3bd8e8f1faed7e15d863ded1fa9460c13db72a13a0daf97

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T00:12:44.687439Z digest=sha256:6c25355526aed38bf2d95ec4213e0bd307872258286f1375078b592ffcdabe81

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:a3efccb53f14c07c833bbf3a2752c3173c457933a9d241a1c65c57cc2b4ea026

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=sha256:1d46d88b48b443766578aeb95cd72049c3ebd01f27f5044004a8e4db355ff423

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T00:12:44.878240Z digest=sha256:0a6cc042d1dfbc1bb9610928ab00154467cfa02c8292b3a9441f5cb70d048255

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T00:12:44.938287Z digest=sha256:fdc2a2b8d182104346693ae12e7f94d09ea511f8d253b50b4813a38893f43184

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=sha256:386edde7b3f3e55f694924e9556466e37cbed082856206c39843b157a16cf5d1

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=sha256:23ad49f761a504d9d280745e44eb287d26962e49419d8fbc5f44f6fe33b12fb8

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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unresolved
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=sha256:75ac157636ac9fc1eb11474dc58676f6976ee3820c7233e675924d962656b1e6

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T00:12:45.212720Z digest=sha256:ecba283e245185bed793a02efa4b9066796f0f87c4aee4b659a48a446ad8747b

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-06T00:12:45.286712Z digest=sha256:472f7be7b8054b085562472d05060c6a033239b7827e01f80bb7e1f5b4b1f00b

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:ec94e40c6dd85f45db98674c6e537d90a5a37a3b4c1ff8574386a9e76557aab3

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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unresolved
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=sha256:954b07223b0f94195745ed329b7cf614f890e5a4ba4328747f9828a96a6b47b8

Pith citing papers

No inbound Pith citation observations are available.