Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies | Paper Citation Record

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This paper cites GPT-4 Technical Report.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies GPT-4 Technical Report

Reference 1

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This paper cites Gemini Overview,.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Gemini Overview,

Reference 2

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This paper cites Introducing Security Copilot,.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Introducing Security Copilot,

Reference 3

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This paper cites Emerging Security Risks with AI,.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Emerging Security Risks with AI,

Reference 4

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This paper cites Dynamic Analysis of Malicious Apps,.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Dynamic Analysis of Malicious Apps,

Reference 5

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This paper cites Automated Code Generation Security Risks,.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Automated Code Generation Security Risks,

Reference 6

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Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Static Analysis Using LLMs,

Reference 7

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This paper cites Risks of LLM Data Leakage,.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Risks of LLM Data Leakage,

Reference 8

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Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Artificial Intelligence Act,

Reference 9

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Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Auto DevSecOps Powered by AI,

Reference 11

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This paper cites Secure Development Lifecycle,.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Secure Development Lifecycle,

Reference 12

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This paper cites Expecting the Unexpected: Failure Modes of LLMs in Software Engineering,.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Expecting the Unexpected: Failure Modes of LLMs in Software Engineering,

Reference 13

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This paper cites Security Copilot Case Study,.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Security Copilot Case Study,

Reference 14

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This paper cites Benchmarking LLM for Zero day Vulnerabilities,.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Benchmarking LLM for Zero day Vulnerabilities,

Reference 15

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This paper cites Why Should I Trust You? Explaining the Predictions of Any Classifier,.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Why Should I Trust You? Explaining the Predictions of Any Classifier,

Reference 18

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This paper cites Explainable Artificial Intelligence,.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Explainable Artificial Intelligence,

Reference 19

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This paper cites Global Challenge for Safe and Secure LLMs Track 1.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Global Challenge for Safe and Secure LLMs Track 1

Reference 20

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Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Policy Enforcement in App Stores,

Reference 21

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Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Static Android Malware Detection,

Reference 22

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Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Fake Review Detection,

Reference 23

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This paper cites Top Cybersecurity Facts, Figures, Predictions, And Statistics For 2025,.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Top Cybersecurity Facts, Figures, Predictions, And Statistics For 2025,

Reference 24

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Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Automated Vulnerability Detection,

Reference 25

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This paper cites Watsonx Security Applications,.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Watsonx Security Applications,

Reference 26

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Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies AIP for Cybersecurity,

Reference 27

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Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies AI Fairness Guidelines,

Reference 28

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Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies AI Risk Management Framework,

Reference 29

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Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Global AI Security Standards,

Reference 30

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Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies SAFE Framework Implementation,

Reference 31

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Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Cybersecurity Almanac: 2024 Edition,

Reference 32

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Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Security, privacy, and compliance for Gemini Code Assist Standard and Enterprise,

Reference 33

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Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Microsoft Security Copilot Frequently Asked Questions,

Reference 34

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This paper cites Use CodeWhisperer to identify issues and use suggestions to improve code security in your IDE,.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Use CodeWhisperer to identify issues and use suggestions to improve code security in your IDE,

Reference 35

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Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Building Production-Ready LLM Systems: Scaling, Moni- toring, and Deployment,

Reference 36

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Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Fairness and Safety of LLMs,

Reference 37

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Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Data Privacy and Compliance for Large Language Models (LLMs),

Reference 38

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Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies What is Large Language Model (LLM) Security,

Reference 39

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Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies What Is Explainable AI (XAI)?,

Reference 40

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Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Fairness Constraints: Mechanisms for Fair Classi- fication,

Reference 41

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Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Barocas, M

Reference 42

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Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Unresolved cited work

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Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies General Data Protection Regulation (GDPR),

Reference 44

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Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies California Consumer Privacy Act (CCPA),

Reference 45

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This paper cites Beyond Accuracy: Behavioral Testing of NLP Models with CheckList,.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Beyond Accuracy: Behavioral Testing of NLP Models with CheckList,

Reference 46

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This paper cites Explainable Artificial Intelligence (XAI),.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Explainable Artificial Intelligence (XAI),

Reference 47

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This paper cites Why Should I Trust You?: Explaining the Predictions of Any Classifier,.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Why Should I Trust You?: Explaining the Predictions of Any Classifier,

Reference 48

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This paper cites A Unified Approach to Interpreting Model Predictions,.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies A Unified Approach to Interpreting Model Predictions,

Reference 49

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Observation bc30cb81-a303-4370-b576-f5e31d6a0507 · outbound

This paper cites Protecting the Whisper: A Security Assessment of Amazon CodeWhisperer’s Generated Code,.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Protecting the Whisper: A Security Assessment of Amazon CodeWhisperer’s Generated Code,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T01:15:50.933575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 01ac3793-3e6b-425c-8db4-5745df604055 · outbound

This paper cites AI Privacy Risks and Mitigations – Large Language Models (LLMs),.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies AI Privacy Risks and Mitigations – Large Language Models (LLMs),

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T01:15:50.938770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2a50c658-b184-4bb9-bc3d-98cc233d62d7 · outbound

This paper cites Explainable AI in Cybersecurity: Bridging Transparency and Trust,.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Explainable AI in Cybersecurity: Bridging Transparency and Trust,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T01:15:50.945372Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation bfd853bb-f03c-40b5-ac91-980f077e551c · outbound

This paper cites CySecBench: A Benchmark Dataset for Evaluating Explainability in Security Contexts,.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies CySecBench: A Benchmark Dataset for Evaluating Explainability in Security Contexts,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T01:15:50.952410Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c3ce0cda-5940-4083-80d6-859463565bdb · outbound

This paper cites CyberMentor: Enhancing Cyber- security Learning through Explainable AI,.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies CyberMentor: Enhancing Cyber- security Learning through Explainable AI,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T01:15:50.930312Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 556294dc-8712-4e2e-8028-75a938feeaa3 · outbound

This paper cites Ethical Auditing in AI: The Role of Model Cards and the Cyber Kill Chain,.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Ethical Auditing in AI: The Role of Model Cards and the Cyber Kill Chain,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T01:15:50.954066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 88a39219-c5f3-4bba-be2e-ab542b428a63 · outbound

This paper cites A Framework for Ethical AI Compliance under the EU AI Act,.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies A Framework for Ethical AI Compliance under the EU AI Act,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T01:15:51.008882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5501ec3c-c38f-4d5d-a943-cd7334196bef · outbound

This paper cites Advances and Open Problems in Federated Learning,.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Advances and Open Problems in Federated Learning,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T01:15:51.011925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 79b85f99-d483-4487-a8f4-efbaa2a03247 · outbound

This paper cites Towards Federated Learning at Scale,.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Towards Federated Learning at Scale,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T01:15:51.013437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 8275a6b6-34a6-496a-9167-41f38a5e1831 · outbound

This paper cites Benchmarking LLMs for Zero Day Vulnerability Detection,.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Benchmarking LLMs for Zero Day Vulnerability Detection,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T01:15:51.015138Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 85ca38cd-0c02-47ae-ba08-b28306aa25d1 · outbound

This paper cites Cooperative Human–AI Collaboration for Secure Software Development,.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Cooperative Human–AI Collaboration for Secure Software Development,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T01:15:51.004761Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 676e097a-a0c0-4be7-86c1-5751dcdc3e3e · outbound

This paper cites Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims

Reference 61

Resolution: metadata mismatch; local_arxiv, observed 2026-07-09T01:15:50.545144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 487ceea8-f148-41a1-a275-32b1c2328349 · outbound

This paper cites Continual lifelong learning with neural networks: A review.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Continual lifelong learning with neural networks: A review

Reference 62

Resolution: verified exact; doi, observed 2026-07-09T01:15:50.408589Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f0dd55a3-b0e1-4266-b489-1bf2acafede8 · outbound

This paper cites COVID-19's Unequal Toll: An assessment of small business impact disparities with respect to ethnorace in metropolitan areas in the US using mobility data.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies COVID-19's Unequal Toll: An assessment of small business impact disparities with respect to ethnorace in metropolitan areas in the US using mobility data

Reference 63

Resolution: metadata mismatch; local_arxiv, observed 2026-07-09T01:15:50.547633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation beb4dbf7-9202-4835-8d70-9936ea979bec · outbound

This paper cites A Watermark for Large Language Models,.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies A Watermark for Large Language Models,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T01:15:51.001919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 200f472b-fe28-4953-a31c-3c44383753fe · outbound

This paper cites State of the Phish Report,.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies State of the Phish Report,

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T01:15:51.006755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f0d5a6af-be46-4aa7-a58a-7937a605f4c0 · outbound

This paper cites The Double-Edged Sword: How Generative AI is Reshaping Cyber Threats,.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies The Double-Edged Sword: How Generative AI is Reshaping Cyber Threats,

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T01:15:51.016982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation df81d50f-824d-4822-9f94-5a16221a2444 · outbound

This paper cites Parameter identification in PDEs by the solution of monotone inclusion problems.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Parameter identification in PDEs by the solution of monotone inclusion problems

Reference 67

Resolution: metadata mismatch; local_arxiv, observed 2026-07-09T01:15:50.552218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3f004a59-0a38-4520-93b1-8c14dae31620 · outbound

This paper cites OW ASP Top 10 for Large Language Model Applications,.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies OW ASP Top 10 for Large Language Model Applications,

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T01:15:50.991061Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 393df60f-9e6d-4dc3-9803-5c3a0705ded0 · outbound

This paper cites Navigating the Intersection of AI and Cybersecurity,.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Navigating the Intersection of AI and Cybersecurity,

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T01:15:50.994299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ca01c4cd-76ac-451e-ad50-28144af66f2e · outbound

This paper cites AI and Cybersecurity: The Evolving Landscape,.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies AI and Cybersecurity: The Evolving Landscape,

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T01:15:50.998068Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation fc233a1a-0a57-42f8-8c4d-43d390a430fa · outbound

This paper cites an unresolved cited work.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Unresolved cited work

Reference 71

Resolution: verified exact; doi, observed 2026-07-09T01:15:50.406372Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 78230095-984e-4a62-9286-2d54c3230736 · outbound

This paper cites Interim Measures for the Man- agement of Generative Artificial Intelligence Services,.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Interim Measures for the Man- agement of Generative Artificial Intelligence Services,

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T01:15:50.982090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a378d707-f9f5-4f29-aebe-17da0f7c5ae4 · outbound

This paper cites AI Strategy 2022,.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies AI Strategy 2022,

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T01:15:50.978844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 21ae9f94-1e6f-4001-bb00-019dc4ab6595 · outbound

This paper cites National Strategy for Artificial Intelligence,.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies National Strategy for Artificial Intelligence,

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T01:15:50.980431Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 6edbfe29-e956-4f39-9ed8-78c2f83b902d · outbound

This paper cites Model AI Governance Framework,.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Model AI Governance Framework,

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T01:15:50.983623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b3868734-0d9f-4216-8b25-280843d4d15c · outbound

This paper cites Database of National AI Strategies and Policies,.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Database of National AI Strategies and Policies,

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T01:15:50.988014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b84bcac1-a829-4ff3-ad4a-06d937ed0560 · outbound

This paper cites Recommendation on the Ethics of Artificial Intelligence,.

Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies Recommendation on the Ethics of Artificial Intelligence,

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T01:15:50.996176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Reference resolution

Outbound references

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