Paper Citation Record · LEDGER

Dynamic Malware Classification of Windows PE Files using CNNs and Greyscale Images Derived from Runtime API Call Argument Conversion

As of 14 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 1 inbound Pith citation observation for arXiv:2505.24231.

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

pith.paper-citation-record.v1
2505.24231 v1

Coverage vector

measured 21 of 21 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:35:02.858857Z

measured 22 of 22 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:50:16.774952Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-07T11:50:17.018938Z

Reference resolution

21 of 21 outbound references displayed

verified exact3
verified fuzzy7
unresolved6
parse uncertain0
malformed identifier2
metadata mismatch3

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f83f394c-e048-4fea-b24a-dd16aa9efe99 · outbound

This paper cites Global Cybersecurity Outlook 2025.

Dynamic Malware Classification of Windows PE Files using CNNs and Greyscale Images Derived from Runtime API Call Argument Conversion Global Cybersecurity Outlook 2025

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:06.857969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation e3b29eab-97af-4747-8882-82340a21fd85 · outbound

This paper cites ”CNN-Based Malware Family Classification and Evaluation.

Dynamic Malware Classification of Windows PE Files using CNNs and Greyscale Images Derived from Runtime API Call Argument Conversion ”CNN-Based Malware Family Classification and Evaluation

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:06.667264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation e1f79b7c-fa13-4ea4-a856-04c83dc4c3e7 · outbound

This paper cites ”Enhancing Malware Classification Through Dynamic Behavioral Anal- ysis, SIEM Integration, and Deep Learning.

Dynamic Malware Classification of Windows PE Files using CNNs and Greyscale Images Derived from Runtime API Call Argument Conversion ”Enhancing Malware Classification Through Dynamic Behavioral Anal- ysis, SIEM Integration, and Deep Learning

Reference 3

Resolution: malformed identifier; raw_fallback, observed 2026-08-07T12:35:05.221649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 8639a42d-1aa7-4433-9fc6-b01bf93d06f5 · outbound

This paper cites ”Visual Malware Classification Using a CNN.” In 2024 IEEE MIT Undergraduate Research Technology Conference (URTC) , pp.

Dynamic Malware Classification of Windows PE Files using CNNs and Greyscale Images Derived from Runtime API Call Argument Conversion ”Visual Malware Classification Using a CNN.” In 2024 IEEE MIT Undergraduate Research Technology Conference (URTC) , pp

Reference 4

Resolution: malformed identifier; raw_fallback, observed 2026-08-07T12:35:04.992896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 2c4690ed-1757-4c16-a3d0-afae317240b1 · outbound

This paper cites Shanmuganathan.

Dynamic Malware Classification of Windows PE Files using CNNs and Greyscale Images Derived from Runtime API Call Argument Conversion Shanmuganathan

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:01.246215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17bc1493-7f85-4561-84a1-bba10bb711d4 · outbound

This paper cites an unresolved cited work.

Dynamic Malware Classification of Windows PE Files using CNNs and Greyscale Images Derived from Runtime API Call Argument Conversion Unresolved cited work

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:01.430653Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3ee46479-aef6-4e7c-92fd-66bcfbd848f3 · outbound

This paper cites ”MVC-RSN: A Malware Classification Method With Variant Identification Ability.

Dynamic Malware Classification of Windows PE Files using CNNs and Greyscale Images Derived from Runtime API Call Argument Conversion ”MVC-RSN: A Malware Classification Method With Variant Identification Ability

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:06.495374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 44ea833a-e798-4c99-92b5-2ab166956c8a · outbound

This paper cites ”IoT Malware Classification Based on Lightweight Convolutional Neural Net- works.

Dynamic Malware Classification of Windows PE Files using CNNs and Greyscale Images Derived from Runtime API Call Argument Conversion ”IoT Malware Classification Based on Lightweight Convolutional Neural Net- works

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:06.279074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 5991d8f6-9c24-42b6-a6a4-fbcfba7e7f89 · outbound

This paper cites Available: https://doi.org/10.1109/JIOT.2024.3436903.

Dynamic Malware Classification of Windows PE Files using CNNs and Greyscale Images Derived from Runtime API Call Argument Conversion Available: https://doi.org/10.1109/JIOT.2024.3436903

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:01.639396Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c231f37f-bdf0-44ba-9f25-fcae66df0947 · outbound

This paper cites ” Mal Class: A Deep Learning Approach for Automatic Classi- fication of Malware Images.” In 2025 4th International Conference on Sentiment Analysis and Deep Learning (ICSADL) , pp.

Dynamic Malware Classification of Windows PE Files using CNNs and Greyscale Images Derived from Runtime API Call Argument Conversion ” Mal Class: A Deep Learning Approach for Automatic Classi- fication of Malware Images.” In 2025 4th International Conference on Sentiment Analysis and Deep Learning (ICSADL) , pp

Reference 10

Resolution: metadata mismatch; raw_fallback, observed 2026-08-07T12:35:04.063335Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 48304a8a-b5c4-461f-bb4b-f877b6395081 · outbound

This paper cites ”Comparative Analysis of Federated Learning, Deep Learning, and Traditional Machine Learning Techniques for IoT Malware Detection.

Dynamic Malware Classification of Windows PE Files using CNNs and Greyscale Images Derived from Runtime API Call Argument Conversion ”Comparative Analysis of Federated Learning, Deep Learning, and Traditional Machine Learning Techniques for IoT Malware Detection

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:02.154984Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b79cf909-77da-4060-8f95-024c480c2ad4 · outbound

This paper cites an unresolved cited work.

Dynamic Malware Classification of Windows PE Files using CNNs and Greyscale Images Derived from Runtime API Call Argument Conversion Unresolved cited work

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:01.916496Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3c2da3f4-b90d-4456-a9ef-dd05381b0158 · outbound

This paper cites ”A Deep Learning Framework for Malware Classification using NLP Techniques.

Dynamic Malware Classification of Windows PE Files using CNNs and Greyscale Images Derived from Runtime API Call Argument Conversion ”A Deep Learning Framework for Malware Classification using NLP Techniques

Reference 13

Resolution: metadata mismatch; raw_fallback, observed 2026-08-07T12:35:03.756634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b35506f3-6e10-4d52-a74b-ec5b6ab5b057 · outbound

This paper cites ”Enhancing Malware Classification with Machine Learning: A Comparative Analysis of API Sequence-Based Techniques.

Dynamic Malware Classification of Windows PE Files using CNNs and Greyscale Images Derived from Runtime API Call Argument Conversion ”Enhancing Malware Classification with Machine Learning: A Comparative Analysis of API Sequence-Based Techniques

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:02.427656Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8453f1ae-18bd-4ed4-bcf6-df0b73e8180f · outbound

This paper cites Manjunath.

Dynamic Malware Classification of Windows PE Files using CNNs and Greyscale Images Derived from Runtime API Call Argument Conversion Manjunath

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:06.116016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 3a908e2a-0683-4bc5-ba28-24a999fb62f2 · outbound

This paper cites VirusShare Malware Repository.

Dynamic Malware Classification of Windows PE Files using CNNs and Greyscale Images Derived from Runtime API Call Argument Conversion VirusShare Malware Repository

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:05.952069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 5babf3c9-7e7e-462c-a161-696eb77c2609 · outbound

This paper cites Automated Malware Analysis.

Dynamic Malware Classification of Windows PE Files using CNNs and Greyscale Images Derived from Runtime API Call Argument Conversion Automated Malware Analysis

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:05.737428Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 4aaa4bf9-c676-4f35-b17c-58314e029ba9 · outbound

This paper cites ”Family Classification of Malicious Applications using Hybrid Analysis and Computationally Economical Machine Learning Techniques.

Dynamic Malware Classification of Windows PE Files using CNNs and Greyscale Images Derived from Runtime API Call Argument Conversion ”Family Classification of Malicious Applications using Hybrid Analysis and Computationally Economical Machine Learning Techniques

Reference 18

Resolution: verified exact; raw_fallback, observed 2026-08-07T12:35:03.407608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation cd6db2f2-7739-4de0-90e0-1be1d8587d53 · outbound

This paper cites Available at: https://doi.org/10.

Dynamic Malware Classification of Windows PE Files using CNNs and Greyscale Images Derived from Runtime API Call Argument Conversion Available at: https://doi.org/10

Reference 21

Resolution: verified exact; raw_fallback, observed 2026-08-07T12:35:03.172703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f2fb6024-d249-4280-920a-4d7003753c4b · outbound

This paper cites Available: https://doi.org/10.1109/JIOT.2021.3100063.

Dynamic Malware Classification of Windows PE Files using CNNs and Greyscale Images Derived from Runtime API Call Argument Conversion Available: https://doi.org/10.1109/JIOT.2021.3100063

Reference 2022

Resolution: metadata mismatch; raw_fallback, observed 2026-08-07T12:35:04.358572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 4b6c368d-0632-46b2-8c05-87b86b954136 · outbound

This paper cites Available: https://doi.org/10.1109/ICEENG58856.2024.

Dynamic Malware Classification of Windows PE Files using CNNs and Greyscale Images Derived from Runtime API Call Argument Conversion Available: https://doi.org/10.1109/ICEENG58856.2024

Reference 2024

Resolution: verified exact; raw_fallback, observed 2026-08-07T12:35:05.495179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Pith citing papers

Observation cdce6cf0-4ef1-4c41-9832-4e7989402d00 · inbound

System Calls for Malware Detection and Classification: Methodologies and Applications cites this paper.

System Calls for Malware Detection and Classification: Methodologies and Applications Dynamic Malware Classification of Windows PE Files using CNNs and Greyscale Images Derived from Runtime API Call Argument Conversion

Reference 26

Resolution: verified exact; local_arxiv, observed 2026-08-07T11:50:17.087064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.