Paper Citation Record · LEDGER

Comparison of Multiple Classifiers for Android Malware Detection with Emphasis on Feature Insights Using CICMalDroid 2020 Dataset

As of 7 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 0 inbound Pith citation observations for arXiv:2602.00058.

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

pith.paper-citation-record.v1
2602.00058 v1

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T09:30:34.606747Z

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

27 of 27 outbound references displayed

verified exact9
verified fuzzy0
unresolved18
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0974b7af-6501-4935-b4aa-e0ced6cc57b2 · outbound

This paper cites Evaluating Ensemble and Deep Learning Models for Static Malware Detection with Dimensionality Reduction Using the EMBER Dataset.

Comparison of Multiple Classifiers for Android Malware Detection with Emphasis on Feature Insights Using CICMalDroid 2020 Dataset Evaluating Ensemble and Deep Learning Models for Static Malware Detection with Dimensionality Reduction Using the EMBER Dataset

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-03T09:30:32.803273Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cca93f31-20a2-42f2-a02b-a9b483425bb6 · outbound

This paper cites Divergence unveils further distinct phenotypic traits of human brain connectomics fingerprint,.

Comparison of Multiple Classifiers for Android Malware Detection with Emphasis on Feature Insights Using CICMalDroid 2020 Dataset Divergence unveils further distinct phenotypic traits of human brain connectomics fingerprint,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-03T09:30:32.850437Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d7f4eee1-a23b-402c-a534-59188ad74e2e · outbound

This paper cites Drebin: Effective and explainable detection of android malware in your pocket,.

Comparison of Multiple Classifiers for Android Malware Detection with Emphasis on Feature Insights Using CICMalDroid 2020 Dataset Drebin: Effective and explainable detection of android malware in your pocket,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-03T09:30:32.896254Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 72807216-9994-463e-98cc-7ce201d687b9 · outbound

This paper cites Droid- sec,.

Comparison of Multiple Classifiers for Android Malware Detection with Emphasis on Feature Insights Using CICMalDroid 2020 Dataset Droid- sec,

Reference 4

Resolution: verified exact; doi, observed 2026-08-03T09:33:57.026222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 91fb44d9-d5f4-495f-a168-41be93da41b9 · outbound

This paper cites Droiddelver: An android malware detection system using deep belief network based on api call blocks,.

Comparison of Multiple Classifiers for Android Malware Detection with Emphasis on Feature Insights Using CICMalDroid 2020 Dataset Droiddelver: An android malware detection system using deep belief network based on api call blocks,

Reference 5

Resolution: verified exact; doi, observed 2026-08-03T09:33:56.850256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b9d81cd3-5be7-4ccd-b614-59de289b217c · outbound

This paper cites Stegopix2pix: Image steganography method via pix2pix networks,.

Comparison of Multiple Classifiers for Android Malware Detection with Emphasis on Feature Insights Using CICMalDroid 2020 Dataset Stegopix2pix: Image steganography method via pix2pix networks,

Reference 6

Resolution: verified exact; doi, observed 2026-08-03T09:33:56.692589Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0d38d924-ed0f-4d70-930e-98f53c861dc6 · outbound

This paper cites Bangla printed character generation from handwritten character using gan,.

Comparison of Multiple Classifiers for Android Malware Detection with Emphasis on Feature Insights Using CICMalDroid 2020 Dataset Bangla printed character generation from handwritten character using gan,

Reference 7

Resolution: verified exact; doi, observed 2026-08-03T09:33:56.503645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation be051db2-3919-49b2-9b0e-9f706e9645b6 · outbound

This paper cites Twssenti: A novel hybrid framework for topic-wise sentiment analysis on social media using transformer models,.

Comparison of Multiple Classifiers for Android Malware Detection with Emphasis on Feature Insights Using CICMalDroid 2020 Dataset Twssenti: A novel hybrid framework for topic-wise sentiment analysis on social media using transformer models,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-03T09:30:33.251913Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a1807ce1-14e9-4e13-a4a2-19221ad875d4 · outbound

This paper cites Classification of android apps and malware using deep neural networks,.

Comparison of Multiple Classifiers for Android Malware Detection with Emphasis on Feature Insights Using CICMalDroid 2020 Dataset Classification of android apps and malware using deep neural networks,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-03T09:30:33.318725Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 99d2ccb0-ef7a-4d2e-ae99-2bf53beeec4e · outbound

This paper cites R2-d2: Color-inspired convolutional neural network (cnn)-based android malware detections,.

Comparison of Multiple Classifiers for Android Malware Detection with Emphasis on Feature Insights Using CICMalDroid 2020 Dataset R2-d2: Color-inspired convolutional neural network (cnn)-based android malware detections,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-03T09:30:33.375285Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation abe8bfe1-fd56-4b59-a90e-f71267f597e9 · outbound

This paper cites Effective android malware detection with a hybrid model based on deep autoencoder and convolutional neural network,.

Comparison of Multiple Classifiers for Android Malware Detection with Emphasis on Feature Insights Using CICMalDroid 2020 Dataset Effective android malware detection with a hybrid model based on deep autoencoder and convolutional neural network,

Reference 11

Resolution: verified exact; doi, observed 2026-08-03T09:33:56.363664Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 77d8941c-c528-4c64-9e6e-a773290be93a · outbound

This paper cites Dysign: Dynamic fingerprinting for the automatic detection of android malware,.

Comparison of Multiple Classifiers for Android Malware Detection with Emphasis on Feature Insights Using CICMalDroid 2020 Dataset Dysign: Dynamic fingerprinting for the automatic detection of android malware,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-03T09:30:33.478268Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d077576-2958-45b0-8573-5b127373f7ea · outbound

This paper cites Droidcat: Effective android malware detection and categorization via app-level profiling,.

Comparison of Multiple Classifiers for Android Malware Detection with Emphasis on Feature Insights Using CICMalDroid 2020 Dataset Droidcat: Effective android malware detection and categorization via app-level profiling,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-03T09:30:33.523100Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d3f05a5e-9d31-41bc-92e0-16c4e50d743f · outbound

This paper cites Android malware detection based on system call sequences and lstm,.

Comparison of Multiple Classifiers for Android Malware Detection with Emphasis on Feature Insights Using CICMalDroid 2020 Dataset Android malware detection based on system call sequences and lstm,

Reference 14

Resolution: verified exact; doi, observed 2026-08-03T09:33:56.180484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6bac9174-3ec2-49db-8253-dbf940f766ff · outbound

This paper cites A multimodal deep learning method for android malware detection using various features,.

Comparison of Multiple Classifiers for Android Malware Detection with Emphasis on Feature Insights Using CICMalDroid 2020 Dataset A multimodal deep learning method for android malware detection using various features,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-03T09:30:33.640670Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 89411bd6-bfbf-4887-83fd-2cdfa1c12b56 · outbound

This paper cites Dynamic android malware category classification using semi-supervised deep learning,.

Comparison of Multiple Classifiers for Android Malware Detection with Emphasis on Feature Insights Using CICMalDroid 2020 Dataset Dynamic android malware category classification using semi-supervised deep learning,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-03T09:30:33.717446Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f45b27e3-60b8-41c0-9c33-70365e759a02 · outbound

This paper cites Android malware detection based on a hybrid deep learning model,.

Comparison of Multiple Classifiers for Android Malware Detection with Emphasis on Feature Insights Using CICMalDroid 2020 Dataset Android malware detection based on a hybrid deep learning model,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-03T09:30:33.757343Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c33d0dff-42af-4358-9878-c5176ab375cf · outbound

This paper cites Active semi-supervised approach for checking app behavior against its description,.

Comparison of Multiple Classifiers for Android Malware Detection with Emphasis on Feature Insights Using CICMalDroid 2020 Dataset Active semi-supervised approach for checking app behavior against its description,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-03T09:30:33.872620Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dd91ed37-8c6e-4905-ab70-e9b3eca77b93 · outbound

This paper cites Detecting and Classifying Android Malware using Static Analysis along with Creator Information.

Comparison of Multiple Classifiers for Android Malware Detection with Emphasis on Feature Insights Using CICMalDroid 2020 Dataset Detecting and Classifying Android Malware using Static Analysis along with Creator Information

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-03T09:30:33.911683Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4a0ad095-9674-40f2-a94b-2e05b9a076fa · outbound

This paper cites Maldozer: Automatic framework for android malware detection using deep learning,.

Comparison of Multiple Classifiers for Android Malware Detection with Emphasis on Feature Insights Using CICMalDroid 2020 Dataset Maldozer: Automatic framework for android malware detection using deep learning,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-03T09:30:33.988743Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 115cb308-ef08-4b6d-8cec-91a1b6dbe2cf · outbound

This paper cites Fossil: A resilient and efficient system for identifying foss functions in malware binaries,.

Comparison of Multiple Classifiers for Android Malware Detection with Emphasis on Feature Insights Using CICMalDroid 2020 Dataset Fossil: A resilient and efficient system for identifying foss functions in malware binaries,

Reference 21

Resolution: verified exact; doi, observed 2026-08-03T09:33:55.626732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4e2e6ca1-7cd2-4264-bdcf-57a0f61f04c7 · outbound

This paper cites Effective and efficient hybrid android malware classification using pseudo- label stacked auto-encoder,.

Comparison of Multiple Classifiers for Android Malware Detection with Emphasis on Feature Insights Using CICMalDroid 2020 Dataset Effective and efficient hybrid android malware classification using pseudo- label stacked auto-encoder,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-03T09:30:34.162280Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e75c67be-f234-4a09-9d18-d8edb852e079 · outbound

This paper cites Amddlmodel: Android smartphones malware detection using deep learning model,.

Comparison of Multiple Classifiers for Android Malware Detection with Emphasis on Feature Insights Using CICMalDroid 2020 Dataset Amddlmodel: Android smartphones malware detection using deep learning model,

Reference 23

Resolution: verified exact; doi, observed 2026-08-03T09:33:55.424498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5cd96b9d-86b2-4972-a8d2-7d3fd6d6cf6a · outbound

This paper cites Benchmarking Android Malware Detection: Traditional vs. Deep Learning Models.

Comparison of Multiple Classifiers for Android Malware Detection with Emphasis on Feature Insights Using CICMalDroid 2020 Dataset Benchmarking Android Malware Detection: Traditional vs. Deep Learning Models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-03T09:30:34.273776Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f466d6f-bbe3-4bf7-aa87-52709611d6b1 · outbound

This paper cites An android mutation malware detection based on deep learning using visualization of importance from codes,.

Comparison of Multiple Classifiers for Android Malware Detection with Emphasis on Feature Insights Using CICMalDroid 2020 Dataset An android mutation malware detection based on deep learning using visualization of importance from codes,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-03T09:30:34.426291Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17514426-0181-4a18-995e-055c0319d81d · outbound

This paper cites Semi-supervised classification for dynamic android malware detection,.

Comparison of Multiple Classifiers for Android Malware Detection with Emphasis on Feature Insights Using CICMalDroid 2020 Dataset Semi-supervised classification for dynamic android malware detection,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-03T09:30:34.606747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 18c13a72-0e03-45bd-9bdd-f29e6286bd5e · outbound

This paper cites Available: /doi/pdf/10.1155/2020/8863617https: //onlinelibrary.wiley.com/doi/abs/10.1155/2020/8863617https: //onlinelibrary.wiley.com/doi/10.1155/2020/8863617.

Comparison of Multiple Classifiers for Android Malware Detection with Emphasis on Feature Insights Using CICMalDroid 2020 Dataset Available: /doi/pdf/10.1155/2020/8863617https: //onlinelibrary.wiley.com/doi/abs/10.1155/2020/8863617https: //onlinelibrary.wiley.com/doi/10.1155/2020/8863617

Reference 2020

Resolution: verified exact; doi, observed 2026-08-03T09:33:55.925640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Pith citing papers

No inbound Pith citation observations are available.