ARCHIVES

1. Yan, Y., Zhang, Y., & Huang, K. (2024). Depending on yourself when you should: Mentoring LLM with RL agents to become the master in cybersecurity games. arXiv preprint arXiv:2403.17674.
2. Tann, W., Liu, Y., Sim, J. H., Seah, C. M., & Chang, E.-C. (2023). Using large language models for cybersecurity capture-the-flag challenges and certification questions. arXiv preprint arXiv:2308.10443.
3. Lira, O. G., Marroquin, A., & To, M. A. (2024). Harnessing the advanced capabilities of LLM for adaptive intrusion detection systems. International Conference on Advanced Information Networking and Applications, Springer, 453–464.
4. Ebert, C., & Beck, M. (2023). Artificial intelligence for cybersecurity. IEEE Software, 40(6), 27–34.
5. Ferrag, M. A., Ndhlovu, M., Tihanyi, N., Cordeiro, L. C., Debbah, M., Lestable, T., & Thandi, N. S. (2024). Revolutionizing cyber threat detection with large language models: A privacy-preserving BERT-based lightweight model for IoT/IIoT devices. IEEE Access.
6. Tihanyi, N., Ferrag, M. A., Jain, R., Bisztray, T., & Debbah, M. (2024). Cybermetric: A benchmark dataset based on retrieval-augmented generation for evaluating LLMs in cybersecurity knowledge. IEEE International Conference on Cyber Security and Resilience (CSR), 296–302.
7. Liu, Z. (2024). A review of advancements and applications of pre-trained language models in cybersecurity. IEEE 12th International Symposium on Digital Forensics and Security (ISDFS), 1–10.
8. Xu, H., Wang, S., Li, N., Zhao, Y., Chen, K., Wang, K., Liu, Y., Yu, T., & Wang, H. (2024). Large language models for cybersecurity: A systematic literature review. arXiv preprint arXiv:2405.04760.
9. Zhang, J., Bu, H., Wen, H., Chen, Y., Li, L., & Zhu, H. (2024). When LLMs meet cybersecurity: A systematic literature review. arXiv preprint arXiv:2405.03644.
10. He, Z., Li, Z., & Yang, S. (2024). Large language models for blockchain security: A systematic literature review. arXiv preprint arXiv:2403.14280.
11. Tian, S., Jin, Q., Yeganova, L., Lai, P.-T., Zhu, Q., Chen, X., Yang, Y., Chen, Q., Kim, W., Comeau, D. C., et al. (2024). Opportunities and challenges for ChatGPT and large language models in biomedicine and health. Briefings in Bioinformatics, 25(1), bbad493.
12. Ferrag, M. A., Friha, O., Hamouda, D., Maglaras, L., & Janicke, H. (2022). Edge-IIoTSet: A new comprehensive realistic cybersecurity dataset of IoT and IIoT applications for centralized and federated learning. IEEE Access, 10, 40281–40306.
13. Hassanin, M., Keshk, M., Salim, S., Alsubaie, M., & Sharma, D. (2025). PLLMCS: Pre-trained large language model (LLM) for cyber threat detection in satellite networks. Ad Hoc Networks, 166, 103645.
14. Saha, D., Tarek, S., Yahyaei, K., Saha, S. K., Zhou, J., Tehranipoor, M., & Farahmandi, F. (2023). LLM for SOC security: A paradigm shift. arXiv preprint arXiv:2310.06046.
15. Fang, R., Bindu, R., Gupta, A., & Kang, D. (2024). LLM agents can autonomously exploit one-day vulnerabilities. arXiv preprint arXiv:2404.08144.
16. K. Jaiswal and A. Vashisth, "A Comprehensive Analysis of UAV Collision Avoidance Techniques for Enhanced Aerial Safety," 2023 4th International Conference on Computation, Automation and Knowledge Management (ICCAKM), Dubai, United Arab Emirates, 2023, pp. 1-6, doi: 10.1109/ICCAKM58659.2023.10449529
17. Mechri, A., Ferrag, M. A., & Debbah, M. (2025). SecureQwen: Leveraging LLMs for vulnerability detection in Python codebases. Computers & Security, 148, 104151.
18. Ding, H., Liu, Y., Piao, X., Song, H., & Ji, Z. (2025). SmartGuard: An LLM-enhanced framework for smart contract vulnerability detection. Expert Systems with Applications, 126479.
19. Wang, J., Yu, L., & Luo, X. (2024). LLMIF: Augmented large language model for fuzzing IoT devices. IEEE Symposium on Security and Privacy (SP), IEEE, 196–196.
20. Liu, P., Sun, C., Zheng, Y., Feng, X., Qin, C., Wang, Y., Xu, Z., Li, Z., Di, P., Jiang, Y., et al. (2025). LLM-powered static binary taint analysis. ACM Transactions on Software Engineering and Methodology.
21. G. Kaur, A. Vashisth and R. S. Batth, "X-Ortho: Fuzzy Rule Based Expert System for Diagnosing Infective Diseases of Hinge Joint Knee,"2019 International Conference on Automation, Computational and Technology Management (ICACTM), London, UK, 2019, pp. 518-524.
22. Vashisth, A., Singh, B., Garg, R. et al. BPACAR: design of a hybrid bioinspired model for dynamic collision-aware routing with continuous pattern analysis in UAV networks. Microsystem Technologies (2023). https://doi.org/10.
23. Anshu Vashisth, Balraj Singh, Ranbir Singh Batth, “QMRNB: Design of an Efficient Q-Learning Model to Improve Routing Efficiency of UAV Networks via Bioinspired Optimizations”, International Journal of Computer Networks and Applications (IJCNA), 10(2), PP: 256-264, 2023, DOI: 10.22247/ijcna/2023/220740.
24. Vashisth, A., Singh, B., & Batth, R. S. (2024). UAV Path Planning: Challenges, Strategies, and Future Directions. In S. Khalid & N. Siddiqui (Eds.), New Innovations in AI, Aviation, and Air Traffic Technology (pp. 150-174). IGI Global. https://doi.org/10.4018/979-8-3693-1954-3.ch008.
25. Kumar, S., Patel, R., & Singh, D. (2024). Zero-day vulnerability detection with LLM-driven automated analysis. Computers & Security, 115, 104212.
26. N. Yadav, G. Kaur, S. Kaur, A. Vashisth and C. Rohith, "A Complete Study on Malware Types and Detecting Ransomware Using API Calls," 2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO), Noida, India, 2021, pp. 1-5, doi: 10.1109/ICRITO51393.2021.9596085.