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Tag: defending
Bibliography items where occurs: 37
- ESR: Ethics and Society Review of Artificial Intelligence Research / 2106.11521 / ISBN:https://doi.org/10.48550/arXiv.2106.11521 / Published by ArXiv / on (web) Publishing site
- References
- A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and Validation / 2305.11391 / ISBN:https://doi.org/10.48550/arXiv.2305.11391 / Published by ArXiv / on (web) Publishing site
- Reference
- Security Considerations in AI-Robotics: A Survey of Current Methods, Challenges, and Opportunities / 2310.08565 / ISBN:https://doi.org/10.48550/arXiv.2310.08565 / Published by ArXiv / on (web) Publishing site
- References
- The Ethics of AI Value Chains / 2307.16787 / ISBN:https://doi.org/10.48550/arXiv.2307.16787 / Published by ArXiv / on (web) Publishing site
- Bibliography
- Moral Responsibility for AI Systems / 2310.18040 / ISBN:https://doi.org/10.48550/arXiv.2310.18040 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
Appendix - Artificial Intelligence Ethics Education in Cybersecurity: Challenges and Opportunities: a
focus group report / 2311.00903 / ISBN:https://doi.org/10.48550/arXiv.2311.00903 / Published by ArXiv / on (web) Publishing site
- Learning Challenges
- Practical Cybersecurity Ethics: Mapping CyBOK to Ethical Concerns / 2311.10165 / ISBN:https://doi.org/10.48550/arXiv.2311.10165 / Published by ArXiv / on (web) Publishing site
- 4 Findings
- Control Risk for Potential Misuse of Artificial Intelligence in Science / 2312.06632 / ISBN:https://doi.org/10.48550/arXiv.2312.06632 / Published by ArXiv / on (web) Publishing site
- References
- The AI Assessment Scale (AIAS): A Framework for Ethical Integration of Generative AI in Educational Assessment / 2312.07086 / ISBN:https://doi.org/10.48550/arXiv.2312.07086 / Published by ArXiv / on (web) Publishing site
- References
- Autonomous Threat Hunting: A Future Paradigm for AI-Driven Threat Intelligence / 2401.00286 / ISBN:https://doi.org/10.48550/arXiv.2401.00286 / Published by ArXiv / on (web) Publishing site
- References
- Detecting Multimedia Generated by Large AI Models: A Survey / 2402.00045 / ISBN:https://doi.org/10.48550/arXiv.2402.00045 / Published by ArXiv / on (web) Publishing site
- References
- Responsible Artificial Intelligence: A Structured Literature Review / 2403.06910 / ISBN:https://doi.org/10.48550/arXiv.2403.06910 / Published by ArXiv / on (web) Publishing site
- 3. Analysis
References - Review of Generative AI Methods in Cybersecurity / 2403.08701 / ISBN:https://doi.org/10.48550/arXiv.2403.08701 / Published by ArXiv / on (web) Publishing site
- References
- Safeguarding Marketing Research: The Generation, Identification, and Mitigation of AI-Fabricated Disinformation / 2403.14706 / ISBN:https://doi.org/10.48550/arXiv.2403.14706 / Published by ArXiv / on (web) Publishing site
- Bibliography
- AI Alignment: A Comprehensive Survey / 2310.19852 / ISBN:https://doi.org/10.48550/arXiv.2310.19852 / Published by ArXiv / on (web) Publishing site
- References
- Epistemic Power in AI Ethics Labor: Legitimizing Located Complaints / 2402.08171 / ISBN:https://doi.org/10.1145/3630106.3658973 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
- AI-Powered Autonomous Weapons Risk Geopolitical Instability and Threaten AI Research / 2405.01859 / ISBN:https://doi.org/10.48550/arXiv.2405.01859 / Published by ArXiv / on (web) Publishing site
- 2. Current State of AWS
References - Integrating Emotional and Linguistic Models for Ethical Compliance in Large Language Models / 2405.07076 / ISBN:https://doi.org/10.48550/arXiv.2405.07076 / Published by ArXiv / on (web) Publishing site
- Appendix S: Multiple Adversarial LLMs
- A Comprehensive Overview of Large Language Models (LLMs) for Cyber Defences: Opportunities and Directions / 2405.14487 / ISBN:https://doi.org/10.48550/arXiv.2405.14487 / Published by ArXiv / on (web) Publishing site
- VII. Cyber Security Operations Automation
- A Survey on Privacy Attacks Against Digital Twin Systems in AI-Robotics / 2406.18812 / ISBN:https://doi.org/10.48550/arXiv.2406.18812 / Published by ArXiv / on (web) Publishing site
- IV. DT-INTEGRATED ROBOTICS DESIGN
CONSIDERATIONS AND DISCUSSION
- RogueGPT: dis-ethical tuning transforms ChatGPT4 into a Rogue AI in 158 Words / 2407.15009 / ISBN:https://doi.org/10.48550/arXiv.2407.15009 / Published by ArXiv / on (web) Publishing site
- References
- AI-Driven Chatbot for Intrusion Detection in Edge Networks: Enhancing Cybersecurity with Ethical User Consent / 2408.04281 / ISBN:https://doi.org/10.48550/arXiv.2408.04281 / Published by ArXiv / on (web) Publishing site
- II. Related Work
- Is Generative AI the Next Tactical Cyber Weapon For Threat Actors? Unforeseen Implications of AI Generated Cyber Attacks / 2408.12806 / ISBN:https://doi.org/10.48550/arXiv.2408.12806 / Published by ArXiv / on (web) Publishing site
- I. Introduction
- Enhancing transparency in AI-powered customer engagement / 2410.01809 / ISBN:https://doi.org/10.48550/arXiv.2410.01809 / Published by ArXiv / on (web) Publishing site
- Go Beyond Algorithms to Enhance Transparency
- Data Defenses Against Large Language Models / 2410.13138 / ISBN:https://doi.org/10.48550/arXiv.2410.13138 / Published by ArXiv / on (web) Publishing site
- 3 Threat Model
4 LLM Adversarial Attacks as LLM Inference Data Defenses
5 Experiments
References - Do LLMs Have Political Correctness? Analyzing Ethical Biases and Jailbreak Vulnerabilities in AI Systems / 2410.13334 / ISBN:https://doi.org/10.48550/arXiv.2410.13334 / Published by ArXiv / on (web) Publishing site
- 3 Methodology PCJAILBREAK
- Jailbreaking and Mitigation of Vulnerabilities in Large Language Models / 2410.15236 / ISBN:https://doi.org/10.48550/arXiv.2410.15236 / Published by ArXiv / on (web) Publishing site
- IV. Defense Mechanisms Against Jailbreak Attacks
V. Evaluation and Benchmarking
References - Smoke Screens and Scapegoats: The Reality of General Data Protection Regulation Compliance -- Privacy and Ethics in the Case of Replika AI / 2411.04490 / ISBN:https://doi.org/10.48550/arXiv.2411.04490 / Published by ArXiv / on (web) Publishing site
- 4. Results
- From Principles to Practice: A Deep Dive into AI Ethics and Regulations / 2412.04683 / ISBN:https://doi.org/10.48550/arXiv.2412.04683 / Published by ArXiv / on (web) Publishing site
- II AI Practice and Contextual Integrity
- Technology as uncharted territory: Contextual integrity and the notion of AI as new ethical ground / 2412.05130 / ISBN:https://doi.org/10.48550/arXiv.2412.05130 / Published by ArXiv / on (web) Publishing site
- II AI Practice and Contextual Integrity
- Towards Friendly AI: A Comprehensive Review and New Perspectives on Human-AI Alignment / 2412.15114 / ISBN:https://doi.org/10.48550/arXiv.2412.15114 / Published by ArXiv / on (web) Publishing site
- IV. Applications
- Large Language Model Safety: A Holistic Survey / 2412.17686 / ISBN:https://doi.org/10.48550/arXiv.2412.17686 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
4 Robustness to Attack
References - Towards Safe AI Clinicians: A Comprehensive Study on Large Language Model Jailbreaking in Healthcare / 2501.18632 / ISBN:https://doi.org/10.48550/arXiv. / Published by ArXiv / on (web) Publishing site
- Abstract
Introduction
Model Guardrail Enhancemen - Safety at Scale: A Comprehensive Survey of Large Model Safety / 2502.05206 / ISBN:https://doi.org/10.48550/arXiv. / Published by ArXiv / on (web) Publishing site
- 4 Vision-Language Pre-Training Model Safety
8 Open Challenges
References - Position: We Need An Adaptive Interpretation of Helpful, Honest, and Harmless Principles / 2502.06059 / ISBN:https://doi.org/10.48550/arXiv. / Published by ArXiv / on (web) Publishing site
- References
- Multi-Agent Risks from Advanced AI / 2502.14143 / ISBN:https://doi.org/10.48550/arXiv.2502.14143 / Published by ArXiv / on (web) Publishing site
- References
- On the Trustworthiness of Generative Foundation Models: Guideline, Assessment, and Perspective / 2502.14296 / ISBN:https://doi.org/10.48550/arXiv.2502.14296 / Published by ArXiv / on (web) Publishing site
- 5 Benchmarking Text-to-Image Models
6 Benchmarking Large Language Models
7 Benchmarking Vision-Language Models
References