Paper Citation Record · LEDGER

RoMA: Robust Malware Attribution via Byte-level Adversarial Training with Global Perturbations and Adversarial Consistency Regularization

As of 10 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2502.07492.

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

pith.paper-citation-record.v1
2502.07492 v2

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T12:37:27.527245Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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

38 of 38 outbound references displayed

verified exact0
verified fuzzy26
unresolved12
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 358d62e4-c679-4074-af82-407882bd0b2d · outbound

This paper cites Structure and Interpretation of Computer Programs.

RoMA: Robust Malware Attribution via Byte-level Adversarial Training with Global Perturbations and Adversarial Consistency Regularization Structure and Interpretation of Computer Programs

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-08T12:37:27.391518Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 93a0ae92-d922-4c1a-bc82-beb60b4e20d1 · outbound

This paper cites Visual information extraction with Lixto.

RoMA: Robust Malware Attribution via Byte-level Adversarial Training with Global Perturbations and Adversarial Consistency Regularization Visual information extraction with Lixto

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-08T12:37:27.395054Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 310b47f6-6ff9-4503-a660-de11b538afc6 · outbound

This paper cites Brachman and James G.

RoMA: Robust Malware Attribution via Byte-level Adversarial Training with Global Perturbations and Adversarial Consistency Regularization Brachman and James G

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-08T12:37:27.398130Z

Source-reported events for the cited work

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Observation a8732689-966c-41d3-821e-fc8402e0349e · outbound

This paper cites Hypertree decompositions and tractable queries.

RoMA: Robust Malware Attribution via Byte-level Adversarial Training with Global Perturbations and Adversarial Consistency Regularization Hypertree decompositions and tractable queries

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-08T12:37:27.401207Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 86367f26-1ad3-4410-b48d-11655bedc72a · outbound

This paper cites Complexity results for nonmonotonic logics.

RoMA: Robust Malware Attribution via Byte-level Adversarial Training with Global Perturbations and Adversarial Consistency Regularization Complexity results for nonmonotonic logics

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-08T12:37:27.404462Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2270ea13-902e-4eb3-90f1-a1d84e704be3 · outbound

This paper cites Levesque.

RoMA: Robust Malware Attribution via Byte-level Adversarial Training with Global Perturbations and Adversarial Consistency Regularization Levesque

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-08T12:37:27.408742Z

Source-reported events for the cited work

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Observation d2855df6-9ed7-4c7b-b48d-e3ca00240b6d · outbound

This paper cites Levesque.

RoMA: Robust Malware Attribution via Byte-level Adversarial Training with Global Perturbations and Adversarial Consistency Regularization Levesque

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-08T12:37:27.413295Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2be4d6d3-196a-462b-910c-fd09d9f24f43 · outbound

This paper cites On the compilability and expressive power of propositional planning formalisms.

RoMA: Robust Malware Attribution via Byte-level Adversarial Training with Global Perturbations and Adversarial Consistency Regularization On the compilability and expressive power of propositional planning formalisms

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-08T12:37:27.417208Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a7951105-0088-4c2b-9ab2-85c234806e08 · outbound

This paper cites Malware Statistics & Trends Report.

RoMA: Robust Malware Attribution via Byte-level Adversarial Training with Global Perturbations and Adversarial Consistency Regularization Malware Statistics & Trends Report

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:37:27.854835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 060cbd09-1024-46c2-aa68-adad14cf1b00 · outbound

This paper cites Towards evaluating the robustness of neural networks.

RoMA: Robust Malware Attribution via Byte-level Adversarial Training with Global Perturbations and Adversarial Consistency Regularization Towards evaluating the robustness of neural networks

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:37:27.843912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4fa67157-51d2-4c1d-9657-ed499423cf40 · outbound

This paper cites Machine learning-enabled IoT security: Open issues and challenges under advanced persistent threats.

RoMA: Robust Malware Attribution via Byte-level Adversarial Training with Global Perturbations and Adversarial Consistency Regularization Machine learning-enabled IoT security: Open issues and challenges under advanced persistent threats

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:37:27.833308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3909d5c8-66d5-443d-9423-68cba9699de4 · outbound

This paper cites Crowdstrike 2024 global threat report.

RoMA: Robust Malware Attribution via Byte-level Adversarial Training with Global Perturbations and Adversarial Consistency Regularization Crowdstrike 2024 global threat report

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:37:27.822264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4a16c22f-f6eb-413b-a9f9-ea1b87d8d592 · outbound

This paper cites ``apt malware dataset".

RoMA: Robust Malware Attribution via Byte-level Adversarial Training with Global Perturbations and Adversarial Consistency Regularization ``apt malware dataset"

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:37:27.811713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e7c0164c-ce51-4b34-9194-e4dc97b635c6 · outbound

This paper cites Adversarial exemples: A survey and experimental evaluation of practical attacks on machine learning for windows malware detection.

RoMA: Robust Malware Attribution via Byte-level Adversarial Training with Global Perturbations and Adversarial Consistency Regularization Adversarial exemples: A survey and experimental evaluation of practical attacks on machine learning for windows malware detection

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:37:27.801347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c8a7a836-8de6-4715-a4ee-cafb7641d8f8 · outbound

This paper cites APTM alinsight: Identify and cognize apt malware based on system call information and ontology knowledge framework.

RoMA: Robust Malware Attribution via Byte-level Adversarial Training with Global Perturbations and Adversarial Consistency Regularization APTM alinsight: Identify and cognize apt malware based on system call information and ontology knowledge framework

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:37:27.790520Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8ac64208-571c-40c8-864a-6e97b2afc4cd · outbound

This paper cites Classifying malwares for identification of author groups.

RoMA: Robust Malware Attribution via Byte-level Adversarial Training with Global Perturbations and Adversarial Consistency Regularization Classifying malwares for identification of author groups

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:37:27.780319Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4a4a54fa-2f19-49b2-96ce-415ca00b2392 · outbound

This paper cites Adversarial malware binaries: Evading deep learning for malware detection in executables.

RoMA: Robust Malware Attribution via Byte-level Adversarial Training with Global Perturbations and Adversarial Consistency Regularization Adversarial malware binaries: Evading deep learning for malware detection in executables

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:37:27.770298Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 092d7617-40e6-4ba4-9f5d-749dd73c356c · outbound

This paper cites Deep convolutional malware classifiers can learn from raw executables and labels only.

RoMA: Robust Malware Attribution via Byte-level Adversarial Training with Global Perturbations and Adversarial Consistency Regularization Deep convolutional malware classifiers can learn from raw executables and labels only

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:37:27.760042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b202b862-c126-4bd5-b3c6-5d444b22c500 · outbound

This paper cites Deep Convolutional Malware Classifiers Can Learn from Raw Executables and Labels Only.

RoMA: Robust Malware Attribution via Byte-level Adversarial Training with Global Perturbations and Adversarial Consistency Regularization Deep Convolutional Malware Classifiers Can Learn from Raw Executables and Labels Only

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:37:27.751267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1010d64d-fdf2-44b3-b58b-1de967e714b9 · outbound

This paper cites Deceiving End-to-End Deep Learning Malware Detectors using Adversarial Examples.

RoMA: Robust Malware Attribution via Byte-level Adversarial Training with Global Perturbations and Adversarial Consistency Regularization Deceiving End-to-End Deep Learning Malware Detectors using Adversarial Examples

Reference 20

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Source-reported events for the cited work

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Observation 0f83a1ba-10fc-40e6-b163-d9bf64434152 · outbound

This paper cites Malware triage for early identification of advanced persistent threat activities.

RoMA: Robust Malware Attribution via Byte-level Adversarial Training with Global Perturbations and Adversarial Consistency Regularization Malware triage for early identification of advanced persistent threat activities

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:37:27.742440Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8e04d143-39ed-473b-b517-56825de273b7 · outbound

This paper cites Adversarial attacks against windows PE malware detection: A survey of the state-of-the-art.

RoMA: Robust Malware Attribution via Byte-level Adversarial Training with Global Perturbations and Adversarial Consistency Regularization Adversarial attacks against windows PE malware detection: A survey of the state-of-the-art

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:37:27.733455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 67226d01-a48e-4d42-97af-2f9ea017e926 · outbound

This paper cites Functions-based CFG embedding for malware homology analysis.

RoMA: Robust Malware Attribution via Byte-level Adversarial Training with Global Perturbations and Adversarial Consistency Regularization Functions-based CFG embedding for malware homology analysis

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:37:27.723944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 421d92d7-e7f8-462a-b1c4-0519608e0257 · outbound

This paper cites Reiter, and Saurabh Shintre.

RoMA: Robust Malware Attribution via Byte-level Adversarial Training with Global Perturbations and Adversarial Consistency Regularization Reiter, and Saurabh Shintre

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:37:27.712985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 653a2ed2-28b3-4dc1-8073-6b0ab233af09 · outbound

This paper cites Reiter, and Mahmood Sharif.

RoMA: Robust Malware Attribution via Byte-level Adversarial Training with Global Perturbations and Adversarial Consistency Regularization Reiter, and Mahmood Sharif

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:37:27.702298Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b8712c5d-fcbc-4138-b1bd-9457be57a3e2 · outbound

This paper cites Towards Deep Learning Models Resistant to Adversarial Attacks.

RoMA: Robust Malware Attribution via Byte-level Adversarial Training with Global Perturbations and Adversarial Consistency Regularization Towards Deep Learning Models Resistant to Adversarial Attacks

Reference 26

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Source-reported events for the cited work

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Observation 17ac83a2-54b2-4d80-b7c7-3d11032cc585 · outbound

This paper cites ``advisory: Turla group exploits iranian apt to expand coverage of victims".

RoMA: Robust Malware Attribution via Byte-level Adversarial Training with Global Perturbations and Adversarial Consistency Regularization ``advisory: Turla group exploits iranian apt to expand coverage of victims"

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:37:27.691612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9c868e4b-0fae-47f3-8c01-ed74916bf750 · outbound

This paper cites Intriguing Properties of Adversarial ML Attacks in the Problem Space.

RoMA: Robust Malware Attribution via Byte-level Adversarial Training with Global Perturbations and Adversarial Consistency Regularization Intriguing Properties of Adversarial ML Attacks in the Problem Space

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:37:27.680824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d126aba5-2b41-478d-b9d3-0cb0b1654a6e · outbound

This paper cites Malware detection by eating a whole exe.

RoMA: Robust Malware Attribution via Byte-level Adversarial Training with Global Perturbations and Adversarial Consistency Regularization Malware detection by eating a whole exe

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:37:27.669737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e8c2c990-606e-464c-9b36-a2aee8e8837a · outbound

This paper cites Classifying sequences of extreme length with constant memory applied to malware detection.

RoMA: Robust Malware Attribution via Byte-level Adversarial Training with Global Perturbations and Adversarial Consistency Regularization Classifying sequences of extreme length with constant memory applied to malware detection

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:37:27.657916Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b5d612fe-6205-4c58-a3b5-a86f3c0277d6 · outbound

This paper cites Bin MLM : Binary Authorship Verification with Flow-aware Mixture-of-Shared Language Model.

RoMA: Robust Malware Attribution via Byte-level Adversarial Training with Global Perturbations and Adversarial Consistency Regularization Bin MLM : Binary Authorship Verification with Flow-aware Mixture-of-Shared Language Model

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:37:27.646882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 775330ea-fc21-413a-b7b4-b5ca5b322cd1 · outbound

This paper cites Towards efficient and effective adversarial training.

RoMA: Robust Malware Attribution via Byte-level Adversarial Training with Global Perturbations and Adversarial Consistency Regularization Towards efficient and effective adversarial training

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:37:27.635577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f3d9eebd-209a-4fc8-8183-0d3aca87bc1a · outbound

This paper cites Mgap3: Malware group attribution based on perceiverio and polytype pre-training.

RoMA: Robust Malware Attribution via Byte-level Adversarial Training with Global Perturbations and Adversarial Consistency Regularization Mgap3: Malware group attribution based on perceiverio and polytype pre-training

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:37:27.624893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 622c338a-ba2a-4df5-bce1-7b546c17b9ce · outbound

This paper cites The Cyberthreat Report.

RoMA: Robust Malware Attribution via Byte-level Adversarial Training with Global Perturbations and Adversarial Consistency Regularization The Cyberthreat Report

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:37:27.613887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 95da9954-c24a-42e1-a727-cd42313658c1 · outbound

This paper cites Visualizing data using t-sne.

RoMA: Robust Malware Attribution via Byte-level Adversarial Training with Global Perturbations and Adversarial Consistency Regularization Visualizing data using t-sne

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-08T12:37:27.518848Z

Source-reported events for the cited work

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Observation 4d2abef7-4dd3-4121-a6d3-291d1faae0ae · outbound

This paper cites VirusSign - Open Malware Database.

RoMA: Robust Malware Attribution via Byte-level Adversarial Training with Global Perturbations and Adversarial Consistency Regularization VirusSign - Open Malware Database

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:37:27.597015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 669f7317-5804-4894-919d-b4a6d2d433d2 · outbound

This paper cites Fast is better than free: Revisiting adversarial training.

RoMA: Robust Malware Attribution via Byte-level Adversarial Training with Global Perturbations and Adversarial Consistency Regularization Fast is better than free: Revisiting adversarial training

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:37:27.586109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 339f2eeb-e557-45d8-9ec5-bd0a5a0486dd · outbound

This paper cites write newline.

RoMA: Robust Malware Attribution via Byte-level Adversarial Training with Global Perturbations and Adversarial Consistency Regularization write newline

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-08T12:37:27.527245Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.