Large Language Models in Cybersecurity
portes grátis
Large Language Models in Cybersecurity
Threats, Exposure and Mitigation
Plancherel, Octave; Mulder, Valentin; Mermoud, Alain; Lenders, Vincent; Kucharavy, Andrei
Springer International Publishing AG
06/2024
247
Dura
9783031548260
15 a 20 dias
Descrição não disponível.
Part I: Introduction.- 1. From Deep Neural Language Models to LLMs.- 2. Adapting LLMs to Downstream Applications.- 3. Overview of Existing LLM Families.- 4. Conversational Agents.- 5. Fundamental Limitations of Generative LLMs.- 6. Tasks for LLMs and their Evaluation.- Part II: LLMs in Cybersecurity.- 7. Private Information Leakage in LLMs.- 8. Phishing and Social Engineering in the Age of LLMs.- 9. Vulnerabilities Introduced by LLMs through Code Suggestions.- 10. LLM Controls Execution Flow Hijacking.- 11. LLM-Aided Social Media Influence Operations.- 12. Deep(er)Web Indexing with LLMs.- Part III: Tracking and Forecasting Exposure.- 13. LLM Adoption Trends and Associated Risks.- 14. The Flow of Investments in the LLM Space.- 15. Insurance Outlook for LLM-Induced Risk.- 16. Copyright-Related Risks in the Creation and Use of ML/AI Systems.- 17. Monitoring Emerging Trends in LLM Research.- Part IV: Mitigation.- 18. Enhancing Security Awareness and Education for LLMs.- 19. Towards Privacy Preserving LLMs Training.- 20. Adversarial Evasion on LLMs.- 21. Robust and Private Federated Learning on LLMs.- 22. LLM Detectors.- 23. On-Site Deployment of LLMs.- 24. LLMs Red Teaming.- 25. Standards for LLM Security.- Part V: Conclusion.- 26. Exploring the Dual Role of LLMs in Cybersecurity: Threats and Defenses.- 27. Towards Safe LLMs Integration.
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Open Access;large language models;cybersecurity;cyberdefense;neural networks;societal implications;risk management;LLMs
Part I: Introduction.- 1. From Deep Neural Language Models to LLMs.- 2. Adapting LLMs to Downstream Applications.- 3. Overview of Existing LLM Families.- 4. Conversational Agents.- 5. Fundamental Limitations of Generative LLMs.- 6. Tasks for LLMs and their Evaluation.- Part II: LLMs in Cybersecurity.- 7. Private Information Leakage in LLMs.- 8. Phishing and Social Engineering in the Age of LLMs.- 9. Vulnerabilities Introduced by LLMs through Code Suggestions.- 10. LLM Controls Execution Flow Hijacking.- 11. LLM-Aided Social Media Influence Operations.- 12. Deep(er)Web Indexing with LLMs.- Part III: Tracking and Forecasting Exposure.- 13. LLM Adoption Trends and Associated Risks.- 14. The Flow of Investments in the LLM Space.- 15. Insurance Outlook for LLM-Induced Risk.- 16. Copyright-Related Risks in the Creation and Use of ML/AI Systems.- 17. Monitoring Emerging Trends in LLM Research.- Part IV: Mitigation.- 18. Enhancing Security Awareness and Education for LLMs.- 19. Towards Privacy Preserving LLMs Training.- 20. Adversarial Evasion on LLMs.- 21. Robust and Private Federated Learning on LLMs.- 22. LLM Detectors.- 23. On-Site Deployment of LLMs.- 24. LLMs Red Teaming.- 25. Standards for LLM Security.- Part V: Conclusion.- 26. Exploring the Dual Role of LLMs in Cybersecurity: Threats and Defenses.- 27. Towards Safe LLMs Integration.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
