Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-06-29T07:15:45.430553Z
Paper Citation Record · LEDGER
As of 17 August 2026, this Paper Citation Record lists 60 of 60 outbound references and 0 inbound Pith citation observations for arXiv:2605.29210.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-06-29T07:15:45.430553Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
60 of 60 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 5a1cbbea-4567-44fe-8024-ae601015c727 · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices Principles and Perspectives in Medical Diagnostic Systems Employing Artificial Intel- ligence (AI) Algorithms,
Reference 1
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Observation a8d416fa-4a56-4bb7-9725-d4cdaac96abc · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices Artificial Intelligence and Machine Learning (AI/ML)-Enabled Medical Devices,
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Observation 3063d471-2f36-4ecb-975e-9e3a4ccd2154 · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices One Drop Blood Glucose Mon- itoring System,
Reference 4
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Observation 6636fe6c-8c55-4753-a099-7115120e7e10 · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices Adversarial Attacks to Machine Learning-Based Smart Healthcare Systems,
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Observation fccc49d3-74eb-4292-8dc8-6adf4c399101 · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices Threats to Training: A Survey of Poisoning Attacks and Defenses on Machine Learning Systems,
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Observation af5e5e0a-26ea-4a06-ae1d-1bd2a97e2098 · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI,
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Observation f95ecff1-fde6-445a-864d-24a9e33879ae · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices Secure and Robust Machine Learning for Healthcare: A Survey,
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Observation f09ac71a-afa0-4876-b2e3-22abc19362c1 · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices Protected or porous: a comparative analysis of threat detection capability of iot safeguards,
Reference 9
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Observation b4686a0c-1235-4adf-b3b8-ea2e276f4d5e · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices A study of data store-based home automation,
Reference 10
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Observation b3a587ea-ec5e-4ec6-b6af-4621ff93a197 · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices Patching up: Stakeholder experiences of security updates for connected medical devices,
Reference 11
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Observation 96a88518-cc54-4310-87f9-d32834f5df79 · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices Discovering and understanding the security hazards in the interactions between{IoT}devices, mobile apps, and clouds on smart home platforms,
Reference 12
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Observation 33cdeb86-ff25-4b44-9f59-c3006c1cbcac · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices Systems-Theoretic and Data-Driven Security Analysis in ML-enabled Medical Devices
Reference 13
Source-reported events for the cited work
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Observation 47754df2-8192-444d-bce6-15d85f21add0 · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices Systems thinking for safety and security,
Reference 14
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Observation fbfb5c48-4f9c-4531-ae3b-ab48c9b00d29 · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices Introduction to stpa-sec,
Reference 15
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Observation 9578f31f-bec3-470f-bb01-026c48434a72 · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices d-Nav System,
Reference 16
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Observation 933c49bd-ab56-4d77-a319-63b7f6a9424b · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices ABMD Software,
Reference 17
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Observation fe5fb626-3c7e-40e7-8ed2-0f14dc98d6af · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices IDx-DR v2.3,
Reference 18
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Observation d56cbef0-6f44-4169-9651-db748c4c091c · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices KIDScore D3,
Reference 19
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Observation cbf3ee2e-169d-483f-bb6d-323e4572d9ba · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices Oxehealth Vital Signs,
Reference 20
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Observation f7b46bd2-7edb-495b-8155-b2d1d2a1b54e · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices Leveson,Engineering a safer world: Systems thinking applied to safety
Reference 21
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Observation 5426fd76-d9bb-45b3-a1f8-2e33253faea3 · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices An stpa primer,
Reference 22
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Observation e954e128-195a-4f12-b8aa-e2ba8e959d30 · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices System-theoretic process analysis for security (STPA-SEC): Cyber security and STPA,
Reference 23
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Observation 1165ec5c-747e-4262-9cce-7cd8d7870164 · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices Integrating autonomous vehicle safety and security analysis using STPA method and the six- step model,
Reference 24
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Observation 02c424d0-bd1e-405e-87ee-05b1c6806593 · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices Safety and Security Analysis of AEB for L4 Autonomous Vehicle Using STPA,
Reference 25
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Observation 4a9b3ce4-ac7f-47d5-90a6-43eec2692703 · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices Sam: Foreseeing inference-time false data injec- tion attacks on ml-enabled medical devices,
Reference 26
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Observation d8cc8bed-e9d5-40e4-825d-af834c6b9f04 · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices Abdulkhaleq and S
Reference 27
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Observation 59908a8c-9d00-456c-8fe5-f02e8ffb188d · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices XSTAMPP: an eXtensible STAMP platform as tool support for safety engineering,
Reference 28
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Observation 9922837c-17ce-44f9-851a-9546023a3f51 · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices Transportation systems safety hazard analysis tool (SafetyHAT) user guide (version 1.0),
Reference 29
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Observation a5bc65e6-c71a-4b0b-a965-5c2edfd63e2c · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices WebSTAMP: A web application for STPA & STPA-Sec,
Reference 30
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Unavailable: canonical work link unavailable.
Observation e5e5d4f9-06d5-48e0-85f7-848e3f692f20 · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices A STAMP-based ontology approach to support safety and security analyses,
Reference 31
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Observation a19d0581-3ab4-4bb7-baaf-ff3565cd4a5a · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices Safety Analysis in the Era of Large Language Models: A Case Study of STPA Using ChatGPT,
Reference 32
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Observation 53c7ca23-0471-4a82-b3fc-c3139c7840b8 · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices Welcome Your New AI Teammate: On Safety Analysis by Leashing Large Language Models,
Reference 33
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Observation e3784463-c9d3-4f18-b128-fc03a6dcb0b5 · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices Engineering Safety Requirements for Autonomous Driving with Large Language Models,
Reference 34
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Observation 31ea4b4c-d52f-4d16-916e-3cb1b3270405 · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices Systematically Assessing the Security Risks of AI/ML-enabled Con- nected Healthcare Systems,
Reference 35
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Observation b6888915-8a57-46cf-94b4-5ef75f053b59 · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices Design and validation of an open-source closed-loop testbed for artificial pancreas systems,
Reference 36
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Observation c7954598-e94d-4f79-abb3-9e02405905f2 · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices Blur- tooth: Exploiting cross-transport key derivation in bluetooth classic and bluetooth low energy,
Reference 37
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Observation 5a2d5340-ed17-4ad8-b463-e0df04193db6 · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices Android source code vulnerability detection: a systematic literature review,
Reference 38
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Observation 6bebd62b-9aa1-4ffd-8a16-4e380078b61d · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices Survey on wireless network security,
Reference 39
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Observation b606a103-a538-43d9-a9a6-ecafee6fc05d · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices Electromagnetic radiofrequency radiation emitted from gsm mobile phones decreases the accuracy of home blood glucose monitors,
Reference 40
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Observation c260a2b5-0fca-4cb7-9738-4343f8386482 · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices Hallucinations in llms: Understanding and addressing challenges,
Reference 41
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Observation dceb740c-98af-4b22-b5d2-bb373ee01c3f · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices Medaiscout: Automated retrieval of known machine learning vulnerabilities in medical applications,
Reference 42
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Observation 25950db6-b53d-417b-8b93-e99830d636ff · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices GLiNER: Generalist model for named entity recognition using bidirectional transformer,
Reference 43
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Observation 474644a7-a329-4c8f-b0df-182fcf017b55 · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices GPT-4 Technical Report
Reference 44
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Observation 707cb7ec-be1e-4de5-bb52-3706eeb8063b · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices Security Vulnerabilities, Attacks, Countermeasures, and Regulations of Networked Medical De- vices—A Review,
Reference 45
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Observation ebb8737b-fef7-4931-a1f1-ece977756922 · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices How ChatGPT and our foundation models are developed,
Reference 46
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Observation 719cd3de-ad20-40b3-9108-fcebf5f726e1 · outbound
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Reference 47
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Observation 8f33c572-c521-4648-b208-25ef99d7ef84 · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices Role play with large language models,
Reference 48
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Observation d3bab11e-8aee-4177-bde2-4ed6f9eebd0a · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices CAMEL: Communicative Agents for
Reference 49
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Observation e036778b-066c-4856-9e09-469396f3029c · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices Teler: A general taxonomy of llm prompts for benchmarking complex tasks,
Reference 50
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Observation c0e3c427-b53e-4523-9df5-e969a7c0212b · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices MITRE ATT&CK
Reference 51
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Observation 387e0f62-2de1-42b7-b398-5ee1ca849ed2 · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices Chain-of-thought prompting elicits reasoning in large language models,
Reference 52
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Observation 82d320aa-e3e4-49aa-8af0-cc83d3abc553 · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices The llama 3 herd of models,
Reference 53
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Observation f3ee7c29-c128-41fd-b2fa-86c97c5015d6 · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices A mathematical investigation of hallucination and creativity in gpt models,
Reference 54
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Observation 648a19f2-6ccc-4036-88b3-4ef10bd291dc · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices Judging llm-as-a-judge with mt-bench and chatbot arena,
Reference 55
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Unavailable: canonical work link unavailable.
Observation 3ae16b24-1dd4-464a-b89a-87c5d41c9ec4 · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices Model Inversion Attacks that Exploit Confidence Information and Basic Countermeasures,
Reference 56
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Observation 52be2be5-b9b7-4852-9b4e-a881dc869caa · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices CT-GAN: Malicious tampering of 3d medical imagery using deep learning,
Reference 57
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Observation 15917018-7827-4b21-8b77-417d0e123ebe · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices Adversarial exposure attack on diabetic retinopathy imagery grading,
Reference 58
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Observation 513aa99e-1b3e-4df2-9563-a655798ca11a · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices Adver- sarial attacks and adversarial robustness in computational pathology,
Reference 59
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Observation aa35da41-0877-46e5-8915-b34b5353aea5 · outbound
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices Adversarial Perturbations Against Real-Time Video Classification Systems
Reference 60
Source-reported events for the cited work
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No inbound Pith citation observations are available.