mlsanityData to 7 Oct 2026

Unveiling Security, Privacy, and Ethical Concerns of ChatGPT

arXiv 2307.14192 ↗First posted 26 Jul 2023cs.CR cs.AIcited by 53

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Abstract (arXiv)

This paper delves into the realm of ChatGPT, an AI-powered chatbot that utilizes topic modeling and reinforcement learning to generate natural responses. Although ChatGPT holds immense promise across various industries, such as customer service, education, mental health treatment, personal productivity, and content creation, it is essential to address its security, privacy, and ethical implications. By exploring the upgrade path from GPT-1 to GPT-4, discussing the model's features, limitations, and potential applications, this study aims to shed light on the potential risks of integrating ChatGPT into our daily lives. Focusing on security, privacy, and ethics issues, we highlight the challenges these concerns pose for widespread adoption. Finally, we analyze the open problems in these areas, calling for concerted efforts to ensure the development of secure and ethically sound large language models.

Key facts. Cited by 53 papers in the map (data through 7 Oct 2026). Builds on 20 of its 38 references that are in the map. First posted on arXiv 26 Jul 2023.

Builds on

20 of 38 references.

References · 20

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2020Language Models are Few-Shot Learnerscited by 32,199
  3. 2023GPT-4 Technical Reportcited by 18,132
  4. 2022Training language models to follow instructions with human feedbackcited by 15,712
  5. 2021Evaluating Large Language Models Trained on Codecited by 8,053
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  11. 2023How Close is ChatGPT to Human Experts? Comparison Corpus, Evaluation, and Detectioncited by 472
  12. 2019Hidden Trigger Backdoor Attackscited by 359
8 more
  1. 2023A Categorical Archive of ChatGPT Failurescited by 167
  2. 2023Generative Language Models and Automated Influence Operations: Emerging Threats and Potential Mitigationscited by 157
  3. 2020MetaPoison: Practical General-purpose Clean-label Data Poisoningcited by 114
  4. 2021Neural Machine Translation for Low-Resource Languages: A Surveycited by 108
  5. 2018iFair: Learning Individually Fair Data Representations for Algorithmic Decision Makingcited by 64
  6. 2022PUMA: Performance Unchanged Model Augmentation for Training Data Removalcited by 56
  7. 2022Deepfake Text Detection: Limitations and Opportunitiescited by 37
  8. 2023Bounding the Capabilities of Large Language Models in Open Text Generation with Prompt Constraintscited by 31

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 5; 2024: 21; 2025: 24; 2026: 3.

53 papers.

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  1. 2023A Survey on Large Language Model (LLM) Security and Privacy: The Good, the Bad, and the Uglycited by 380
  2. 2024A Survey on Knowledge Distillation of Large Language Modelscited by 276
  3. 2024Security and Privacy Challenges of Large Language Models: A Surveycited by 179
  4. 2024LLM Dataset Inference: Did you train on my dataset?cited by 107
  5. 2024NYU CTF Bench: A Scalable Open-Source Benchmark Dataset for Evaluating LLMs in Offensive Securitycited by 90
  6. 2024A New Era in LLM Security: Exploring Security Concerns in Real-World LLM-based Systemscited by 74
  7. 2024Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systemscited by 63
  8. 2023Towards Possibilities & Impossibilities of AI-generated Text Detection: A Surveycited by 28
  9. 2024Navigating LLM Ethics: Advancements, Challenges, and Future Directionscited by 28
  10. 2024Mapping the Ethics of Generative AI: A Comprehensive Scoping Reviewcited by 19
  11. 2025D-CIPHER: Dynamic Collaborative Intelligent Multi-Agent System with Planner and Heterogeneous Executors for Offensive Securitycited by 19
  12. 2024Text Generation: A Systematic Literature Review of Tasks, Evaluation, and Challengescited by 18
38 more
  1. 2025CRAKEN: Cybersecurity LLM Agent with Knowledge-Based Executioncited by 14
  2. 2025Using Vision Language Models for Safety Hazard Identification in Constructioncited by 12
  3. 2023Are Chatbots Reliable Text Annotators? Sometimescited by 9
  4. 2024The Phantom Menace: Unmasking Privacy Leakages in Vision-Language Modelscited by 8
  5. 2024Risks, Causes, and Mitigations of Widespread Deployments of Large Language Models (LLMs): A Surveycited by 8
  6. 2024LlamaDuo: LLMOps Pipeline for Seamless Migration from Service LLMs to Small-Scale Local LLMscited by 8
  7. 2025Unlocking Post-hoc Dataset Inference with Synthetic Datacited by 7
  8. 2025Student Perspectives on the Benefits and Risks of AI in Educationcited by 6
  9. 2023SoK: Access Control Policy Generation from High-level Natural Language Requirementscited by 5
  10. 2024RAGent: Retrieval-based Access Control Policy Generationcited by 5
  11. 2024SoK: Prompt Hacking of Large Language Modelscited by 5
  12. 2024Exactly Minimax-Optimal Locally Differentially Private Samplingcited by 5
  13. 2025Tag&Tab: Pretraining Data Detection in Large Language Models Using Keyword-Based Membership Inference Attackcited by 5
  14. 2025EfficientNav: Towards On-Device Object-Goal Navigation with Navigation Map Caching and Retrievalcited by 5
  15. 2024Generative AI Security: Challenges and Countermeasurescited by 4
  16. 2025Function-to-Style Guidance of LLMs for Code Translationcited by 4
  17. 2025Secure and Robust Watermarking for AI-generated Images: A Comprehensive Surveycited by 4
  18. 2024Large Language Model Agents for Improving Engagement with Behavior Change Interventions: Application to Digital Mindfulnesscited by 3
  19. 2025Can Media Act as a Soft Regulator of Safe AI Development? A Game Theoretical Analysiscited by 3
  20. 2025A Statistical Hypothesis Testing Framework for Data Misappropriation Detection in Large Language Modelscited by 2
  21. 2025SOK: Exploring Hallucinations and Security Risks in AI-Assisted Software Development with Insights for LLM Deploymentcited by 2
  22. 2025Automatic Calibration for Membership Inference Attack on Large Language Modelscited by 2
  23. 2025A Survey on Foundation Models for Personalized Federated Intelligencecited by 2
  24. 2025When There Is No Decoder: Removing Watermarks from Stable Diffusion Models in a No-box Settingcited by 2
  25. 2025Securing Educational LLMs: A Generalised Taxonomy of Attacks on LLMs and DREAD Risk Assessmentcited by 2
  26. 2025Universal and Transferable Adversarial Attack on Large Language Models Using Exponentiated Gradient Descentcited by 2
  27. 2025Direct Token Optimization: A Self-contained Approach to Large Language Model Unlearningcited by 2
  28. 2025A Longitudinal Measurement of Privacy Policy Evolution for Large Language Modelscited by 2
  29. 2023Are You Worthy of My Trust?: A Socioethical Perspective on the Impacts of Trustworthy AI Systems on the Environment and Human Societycited by 1
  30. 2024The Evolution of Learning: Assessing the Transformative Impact of Generative AI on Higher Educationcited by 1
  31. 2024An Empirical Design Justice Approach to Identifying Ethical Considerations in the Intersection of Large Language Models and Social Roboticscited by 1
  32. 2024Evaluating the capability of large language models to personalize science texts for diverse middle-school-age learnerscited by 1
  33. 2025LexiMark: Robust Watermarking via Lexical Substitutions to Enhance Membership Verification of an LLM's Textual Training Datacited by 1
  34. 2024AI-Empowered Human Research Integrating Brain Science and Social Sciences Insightscited by 0
  35. 2025Large Language Models' Accuracy in Emulating Human Experts' Evaluation of Public Sentiments about Heated Tobacco Products on Social Mediacited by 0
  36. 2025Contextual Embedding-based Clustering to Identify Topics for Healthcare Service Improvementcited by 0
  37. 2025When Explainability Meets Privacy: An Investigation at the Intersection of Post-hoc Explainability and Differential Privacy in the Context of Natural Language Processingcited by 0
  38. 2025Generative AI in Heritage Practice: Improving the Accessibility of Heritage Guidancecited by 0

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