Research proposal ideas focusing on the security, robustness, and trustworthiness of AI:

Research proposal ideas focusing on the security, robustness, and trustworthiness of AI:

1. Adversarial robustness of deep learning models in cybersecurity applications[1][3]

   - Investigating techniques to make AI models more resilient against adversarial attacks in security-critical domains

2. Explainable AI for intrusion detection systems[1][3]

   - Developing interpretable AI models for network security that can provide clear explanations for their decisions

3. Privacy-preserving machine learning for collaborative threat intelligence[1][3]

   - Exploring federated learning and other privacy-enhancing technologies to enable secure sharing of threat data across organizations

4. Ethical considerations in AI-powered vulnerability scanning and penetration testing[1][3]

   - Addressing the ethical implications and potential misuse of AI in offensive security tools

5. Quantum-resistant machine learning algorithms for cryptography[1][3]

   - Designing AI models that remain secure in the face of potential quantum computing threats

6. Bias detection and mitigation in AI-based security decision systems[1][3]

   - Developing methods to identify and reduce biases in AI models used for security-related decision-making

7. Trustworthy AI for autonomous cyber defense systems[1][3]

   - Creating reliable and verifiable AI agents for automated incident response and threat mitigation

8. Robustness of AI models against data poisoning attacks in security applications[1][3]

   - Investigating techniques to protect machine learning models from malicious manipulation of training data

9. Secure multi-party computation for privacy-preserving AI in cybersecurity[1][3]

   - Exploring cryptographic techniques to enable collaborative AI training and inference without compromising data privacy

10. AI-powered deception technologies for cyber defense[1][3]

    - Developing intelligent honeypots and other deception mechanisms to detect and mislead attackers

11. Formal verification of AI systems in safety-critical security applications[1][3]

    - Applying formal methods to prove the correctness and security properties of AI models in high-stakes environments

12. Continuous learning and adaptation of AI models in evolving threat landscapes[1][3]

    - Designing AI systems that can securely update and improve their performance as new cyber threats emerge

These research proposal ideas address various aspects of AI security, robustness, and trustworthiness in the context of cybersecurity. They aim to tackle critical challenges in ensuring that AI systems used for security purposes are reliable, resistant to attacks, and ethically sound.

Citations:

[1] https://slogix.in/cybersecurity/latest-research-papers-in-artificial-intelligence-for-cyber-security-threats/

[2] https://www.researchgate.net/post/Which_of_these_topics_would_be_best_to_do_a_PhD_thesis_on

[3] https://www.knowledgehut.com/blog/security/cyber-security-research-topics

[4] https://ihsonline.org/research/research-proposals

[5] https://www.reddit.com/r/cybersecurity/comments/1abgm6g/ideas_for_ai_in_cybersecurity/