Paper Citation Record · LEDGER

MARD: A Multi-Agent Framework for Robust Android Malware Detection

As of 31 July 2026, this Paper Citation Record lists 49 of 49 outbound references and 1 inbound Pith citation observation for arXiv:2604.25264.

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

pith.paper-citation-record.v1
2604.25264 v1

Coverage vector

measured 49 of 49 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-07T15:59:46.278812Z

measured 50 of 50 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-07-31T06:34:12.847434+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-13T04:53:04.033865Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

49 of 49 outbound references displayed

verified exact0
verified fuzzy48
unresolved1
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a00fdd18-4da4-46d5-ba1e-249aac458185 · outbound

This paper cites Android security: a survey of issues, malware penetration, and defenses.IEEE communications surveys & tutorials, 17(2):998–1022.

MARD: A Multi-Agent Framework for Robust Android Malware Detection Android security: a survey of issues, malware penetration, and defenses.IEEE communications surveys & tutorials, 17(2):998–1022

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.546298Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 6f0647ee-5bb9-4332-9e76-834ec15c63d1 · outbound

This paper cites A survey on various threats and current state of security in android platform.ACM Computing Surveys (CSUR), 52(1):1–35.

MARD: A Multi-Agent Framework for Robust Android Malware Detection A survey on various threats and current state of security in android platform.ACM Computing Surveys (CSUR), 52(1):1–35

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.516926Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 957dd0b4-df64-400e-8487-495c9a322001 · outbound

This paper cites Crowdroid: behavior-based malware detection system for android.

MARD: A Multi-Agent Framework for Robust Android Malware Detection Crowdroid: behavior-based malware detection system for android

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.520523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation ed5dd66f-c7e4-42ae-9540-cb7ce22d7226 · outbound

This paper cites Droid- sec: deep learning in android malware detection.

MARD: A Multi-Agent Framework for Robust Android Malware Detection Droid- sec: deep learning in android malware detection

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.549810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 87b521af-ffbe-4e55-968b-1c994c6e86a7 · outbound

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

MARD: A Multi-Agent Framework for Robust Android Malware Detection Drebin: Effective and explainable detection of android malware in your pocket

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.557456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 7871d875-3a80-45b0-b39a-e4b90f4bed6b · outbound

This paper cites Transcend: Detecting concept drift in malware classification models.

MARD: A Multi-Agent Framework for Robust Android Malware Detection Transcend: Detecting concept drift in malware classification models

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.561015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation dea82289-fc08-4ac2-a2d3-bf96c2011a1a · outbound

This paper cites Transcending transcend: Revisiting malware classification in the presence of concept drift.

MARD: A Multi-Agent Framework for Robust Android Malware Detection Transcending transcend: Revisiting malware classification in the presence of concept drift

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.505216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 762de67e-bd76-42a8-90c8-367a4629d5fd · outbound

This paper cites Cyber code intelligence for android malware detection.IEEE Transactions on Cybernetics, 53(1):617–627.

MARD: A Multi-Agent Framework for Robust Android Malware Detection Cyber code intelligence for android malware detection.IEEE Transactions on Cybernetics, 53(1):617–627

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.501116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 37dfabe5-6cbe-409d-ac3e-691537d683c0 · outbound

This paper cites Droidapiminer: Mining api- level features for robust malware detection in android.

MARD: A Multi-Agent Framework for Robust Android Malware Detection Droidapiminer: Mining api- level features for robust malware detection in android

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.493254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation fdcff3f1-cc55-4ec0-bfb5-530fe0b0144e · outbound

This paper cites Intelligent mobile malware detection using permission requests and api calls.Future Generation Computer Systems, 107:509–521.

MARD: A Multi-Agent Framework for Robust Android Malware Detection Intelligent mobile malware detection using permission requests and api calls.Future Generation Computer Systems, 107:509–521

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.497277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation bf4434dc-bb8c-49d8-af8b-12b432ed0cbe · outbound

This paper cites Cruparamer: Learning on parameter-augmented api sequences for malware detection.IEEE Transactions on Information Forensics and Security, 17:788–803.

MARD: A Multi-Agent Framework for Robust Android Malware Detection Cruparamer: Learning on parameter-augmented api sequences for malware detection.IEEE Transactions on Information Forensics and Security, 17:788–803

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.512771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 3312cc91-cb3b-4ea8-8e76-b350e9f9f3aa · outbound

This paper cites Significant permission identification for machine-learning- based android malware detection.IEEE Transactions on Industrial Informatics, 14(7):3216–3225.

MARD: A Multi-Agent Framework for Robust Android Malware Detection Significant permission identification for machine-learning- based android malware detection.IEEE Transactions on Industrial Informatics, 14(7):3216–3225

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.489431Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 2b9f09f5-5555-4664-8f9e-5ba71dc61507 · outbound

This paper cites Improved real- time permission based malware detection and clustering approach using model independent pruning.IET Information Security, 14(5):531–541.

MARD: A Multi-Agent Framework for Robust Android Malware Detection Improved real- time permission based malware detection and clustering approach using model independent pruning.IET Information Security, 14(5):531–541

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.479276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation a40abd93-74fe-4e5f-80cc-6ea5848f19bf · outbound

This paper cites Malscan: Fast market-wide mobile malware scanning by social-network centrality analysis.

MARD: A Multi-Agent Framework for Robust Android Malware Detection Malscan: Fast market-wide mobile malware scanning by social-network centrality analysis

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.472058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 8fb3883d-8268-4a3e-a537-2844c89005a4 · outbound

This paper cites Learn- ing features from enhanced function call graphs for android malware detection.Neurocomputing, 423:301–307.

MARD: A Multi-Agent Framework for Robust Android Malware Detection Learn- ing features from enhanced function call graphs for android malware detection.Neurocomputing, 423:301–307

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.475581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 1454a136-74cf-4a91-8c55-7784126e6edb · outbound

This paper cites Dmalnet: Dynamic malware analysis based on api feature engineering and graph learning.Computers & Security, 122:102872.

MARD: A Multi-Agent Framework for Robust Android Malware Detection Dmalnet: Dynamic malware analysis based on api feature engineering and graph learning.Computers & Security, 122:102872

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.484829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation fa9c53b2-e280-42e6-b2b6-a51511004e3d · outbound

This paper cites Demystifying the evolution of android malware variants.IEEE Transactions on Dependable and Secure Computing, 21(4):3324–3341.

MARD: A Multi-Agent Framework for Robust Android Malware Detection Demystifying the evolution of android malware variants.IEEE Transactions on Dependable and Secure Computing, 21(4):3324–3341

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.508945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 49662c97-569e-43ed-a67b-212716783ba4 · outbound

This paper cites Machine learning for android malware detection: mission accomplished? a comprehensive review of open challenges and future perspectives.Computers & Security, 138:103654.

MARD: A Multi-Agent Framework for Robust Android Malware Detection Machine learning for android malware detection: mission accomplished? a comprehensive review of open challenges and future perspectives.Computers & Security, 138:103654

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.458286Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 2ef98c26-1a25-4c9a-a414-28dfac30174e · outbound

This paper cites Mamadroid: Detect- ing android malware by building markov chains of behavioral models (extended version).ACM Transactions on Privacy and Security (TOPS), 22(2):1–34.

MARD: A Multi-Agent Framework for Robust Android Malware Detection Mamadroid: Detect- ing android malware by building markov chains of behavioral models (extended version).ACM Transactions on Privacy and Security (TOPS), 22(2):1–34

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.468624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation a0628077-7a15-4fc8-90af-3e942e164966 · outbound

This paper cites Sdac: A slow-aging solution for android malware detection using semantic distance based api clustering.IEEE transactions on dependable and secure computing, 19(2):1149–1163.

MARD: A Multi-Agent Framework for Robust Android Malware Detection Sdac: A slow-aging solution for android malware detection using semantic distance based api clustering.IEEE transactions on dependable and secure computing, 19(2):1149–1163

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.445706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation d797778a-cfc1-483a-ad5a-2ac949ec3307 · outbound

This paper cites Slowing down the aging of learning- based malware detectors with api knowledge.IEEE Transactions on Dependable and Secure Computing, 20(2):902–916.

MARD: A Multi-Agent Framework for Robust Android Malware Detection Slowing down the aging of learning- based malware detectors with api knowledge.IEEE Transactions on Dependable and Secure Computing, 20(2):902–916

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.449002Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 611d2664-8f36-47f7-ad9b-44ca3f635e21 · outbound

This paper cites A novel android malware detection method with api semantics extraction.

MARD: A Multi-Agent Framework for Robust Android Malware Detection A novel android malware detection method with api semantics extraction

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.442126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation f3e77f30-0883-4071-abee-141c8cf85766 · outbound

This paper cites Ldcdroid: Learning data drift characteristics for handling the model aging problem in android malware detection.

MARD: A Multi-Agent Framework for Robust Android Malware Detection Ldcdroid: Learning data drift characteristics for handling the model aging problem in android malware detection

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.438988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 4fe3d772-bc1a-41c3-a633-098ad69c6036 · outbound

This paper cites In30th USENIX Security Symposium (USENIX Security 21), pages 2327–2344.

MARD: A Multi-Agent Framework for Robust Android Malware Detection In30th USENIX Security Symposium (USENIX Security 21), pages 2327–2344

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.451866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 4bf4845b-9d51-4ba5-a060-16140f5a90c9 · outbound

This paper cites Fesad ransomware detection framework with machine learning using adaption to concept drift.Computers & Security, 137:103629.

MARD: A Multi-Agent Framework for Robust Android Malware Detection Fesad ransomware detection framework with machine learning using adaption to concept drift.Computers & Security, 137:103629

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.464971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 334e7ce0-b506-47e7-8a2e-412e78a83093 · outbound

This paper cites Droide- volver: Self-evolving android malware detection system.

MARD: A Multi-Agent Framework for Robust Android Malware Detection Droide- volver: Self-evolving android malware detection system

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.435522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation adf5add9-4af0-489f-b552-a0135dbec658 · outbound

This paper cites Strengthening llm ecosystem security: Preventing mobile malware from manipulating llm-based applications.Information Sciences, 681:120923.

MARD: A Multi-Agent Framework for Robust Android Malware Detection Strengthening llm ecosystem security: Preventing mobile malware from manipulating llm-based applications.Information Sciences, 681:120923

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.461619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation ef874d37-c66c-4624-be13-c7f21a54bc2f · outbound

This paper cites Continuous learning for android malware detection.

MARD: A Multi-Agent Framework for Robust Android Malware Detection Continuous learning for android malware detection

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.454648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 0e61266d-e416-40cb-8639-206f271f889a · outbound

This paper cites Plangenllms: A modern survey of llm planning capabilities.

MARD: A Multi-Agent Framework for Robust Android Malware Detection Plangenllms: A modern survey of llm planning capabilities

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.553835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 1492e283-c45c-4695-ac16-9751c5ed6f68 · outbound

This paper cites Srdc: Semantics- based ransomware detection and classification with llm-assisted pre- training.

MARD: A Multi-Agent Framework for Robust Android Malware Detection Srdc: Semantics- based ransomware detection and classification with llm-assisted pre- training

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.620577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation bb91bcf4-e532-4be2-b196-28c28107c5bd · outbound

This paper cites Apppoet: Large language model based android malware detection via multi-view prompt engineering.Expert Systems with Applications, 262:125546.

MARD: A Multi-Agent Framework for Robust Android Malware Detection Apppoet: Large language model based android malware detection via multi-view prompt engineering.Expert Systems with Applications, 262:125546

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.616434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 1baae9f1-e0a4-435f-9355-738e8de95b45 · outbound

This paper cites Foredroid: Scenario-aware analysis for android malware detection and explanation.

MARD: A Multi-Agent Framework for Robust Android Malware Detection Foredroid: Scenario-aware analysis for android malware detection and explanation

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.624495Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation df8c5c8e-b9c1-436c-a24b-79ce6e874d1b · outbound

This paper cites Prompt engineering-assisted malware dynamic analysis using gpt-4.IEEE Transactions on Dependable and Secure Computing.

MARD: A Multi-Agent Framework for Robust Android Malware Detection Prompt engineering-assisted malware dynamic analysis using gpt-4.IEEE Transactions on Dependable and Secure Computing

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.628737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation a495d4e3-e06f-4e7f-a8f6-5b83cb78017f · outbound

This paper cites Av-agent: A bottom- up interpretable malware classifier based on large language models.

MARD: A Multi-Agent Framework for Robust Android Malware Detection Av-agent: A bottom- up interpretable malware classifier based on large language models

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.632603Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation b5dacf22-0d8f-4eaf-878e-db2a20893337 · outbound

This paper cites On benchmarking code llms for android malware analysis.

MARD: A Multi-Agent Framework for Robust Android Malware Detection On benchmarking code llms for android malware analysis

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.609151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation c2448c8e-44f9-4f98-9227-2a7a3779b01a · outbound

This paper cites Lamd: Context-driven android malware detection and classification with llms.

MARD: A Multi-Agent Framework for Robust Android Malware Detection Lamd: Context-driven android malware detection and classification with llms

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.605553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation fdb58dee-eec1-4f5e-8136-1e208fdf14ba · outbound

This paper cites Api2vec: Learning representations of api sequences for malware detection.

MARD: A Multi-Agent Framework for Robust Android Malware Detection Api2vec: Learning representations of api sequences for malware detection

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.593628Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 1a382b2f-84eb-447e-9d0a-5230809cba6e · outbound

This paper cites Apibeh: Learning behavior inclination of apis for malware classification.

MARD: A Multi-Agent Framework for Robust Android Malware Detection Apibeh: Learning behavior inclination of apis for malware classification

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.597174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 473bf623-99e6-4b07-a82c-802cd8ffb447 · outbound

This paper cites Appcontext: Differentiating malicious and benign mobile app behaviors using context.

MARD: A Multi-Agent Framework for Robust Android Malware Detection Appcontext: Differentiating malicious and benign mobile app behaviors using context

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.601340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 2055b444-80d4-407c-977b-6a4ec1c6df68 · outbound

This paper cites Android malware classification and optimisation based on bm25 score of android api.

MARD: A Multi-Agent Framework for Robust Android Malware Detection Android malware classification and optimisation based on bm25 score of android api

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.612703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 57700bd4-1a42-4c6c-a036-c364ea3f2da8 · outbound

This paper cites A multimodal deep learning method for android malware detection using various features.IEEE Transactions on Information Forensics and Security, 14(3):773–788.

MARD: A Multi-Agent Framework for Robust Android Malware Detection A multimodal deep learning method for android malware detection using various features.IEEE Transactions on Information Forensics and Security, 14(3):773–788

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.636991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 3ea2be6f-b1b6-4e7c-8400-e0216ff249b2 · outbound

This paper cites Jowmdroid: Android malware detection based on feature weighting with joint optimization of weight- mapping and classifier parameters.Computers & Security, 100:102086.

MARD: A Multi-Agent Framework for Robust Android Malware Detection Jowmdroid: Android malware detection based on feature weighting with joint optimization of weight- mapping and classifier parameters.Computers & Security, 100:102086

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.583707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 79aa4fd2-2d0b-430a-83dc-fc11fa70d5f3 · outbound

This paper cites Mobipcr: Efficient, accurate, and strict ml-based mobile malware detection.Future Generation Computer Systems, 144:140–150.

MARD: A Multi-Agent Framework for Robust Android Malware Detection Mobipcr: Efficient, accurate, and strict ml-based mobile malware detection.Future Generation Computer Systems, 144:140–150

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.579861Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 1e73cf9e-01ac-4948-a8d5-472f8ee7df96 · outbound

This paper cites Fesa: Feature selection architecture for ransomware detection under concept drift.Computers & Security, 116:102659.

MARD: A Multi-Agent Framework for Robust Android Malware Detection Fesa: Feature selection architecture for ransomware detection under concept drift.Computers & Security, 116:102659

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.587214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 73b40892-ffe5-4044-b6bc-f69befbe00bb · outbound

This paper cites an unresolved cited work.

MARD: A Multi-Agent Framework for Robust Android Malware Detection Unresolved cited work

Reference 45

Resolution: unresolved; raw_fallback, observed 2026-05-27T02:43:27.572392Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 6b67c60d-4155-4ab3-9302-11acca7f0dab · outbound

This paper cites Poster: Llmalware: An llm-powered robust and efficient android malware detec- tion framework.

MARD: A Multi-Agent Framework for Robust Android Malware Detection Poster: Llmalware: An llm-powered robust and efficient android malware detec- tion framework

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.565382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 15cd89f2-18a1-410d-b7d5-d30e5fe70865 · outbound

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

MARD: A Multi-Agent Framework for Robust Android Malware Detection Dynamic android malware category classification using semi-supervised deep learning

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.569055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation 8ba5de07-2a09-457d-813d-352c11e07891 · outbound

This paper cites Bissyand ´e, Jacques Klein, and Yves Le Traon.

MARD: A Multi-Agent Framework for Robust Android Malware Detection Bissyand ´e, Jacques Klein, and Yves Le Traon

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.575825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Observation eb3fad6b-033b-41d6-9cdc-63dd8dfb9cbb · outbound

This paper cites Toward developing a systematic approach to generate bench- mark android malware datasets and classification.

MARD: A Multi-Agent Framework for Robust Android Malware Detection Toward developing a systematic approach to generate bench- mark android malware datasets and classification

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-05-27T02:43:27.590538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.

Pith citing papers

Observation 87c20f2d-c791-4425-8558-95a7ec425261 · inbound

Malaika: Understanding Malware through Tri-Grounded Agentic Reasoning cites this paper.

Malaika: Understanding Malware through Tri-Grounded Agentic Reasoning MARD: A Multi-Agent Framework for Robust Android Malware Detection

Reference 44

Resolution: unresolved; no resolver link, observed 2026-07-13T04:53:04.033865Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.