Mst Shapna Akter, Ph.D.

Assistant Professor Department of Computer Science and Engineering akter@oakland.edu https://mstakter486-prog.github.io/security-lab/ Ph.D., Intelligent Systems and Robotics, University of West Florida

Teaching

• Natural Language Processing (CSI 4180/5180)
• Cyber Law and Digital Forensics (CSI 4740/5740)
• IT Project Management (CSI 4430/5430)
• Database Systems I (CSI 4450/5450)
• Script Programming (CSI 3680)
• Introduction to Data Structures in C (CSI 2290)
• Senior Capstone Project (CSI 4999)

Research

• Software vulnerability detection using large language models (LLMs)
• Code-focused pretrained models (CodePTMs), parameter-efficient adaptation, and efficient AI for software security
• Neuro-symbolic AI for vulnerability detection and mitigation
• Cybersecurity datasets, label reliability, and cross-dataset/cross-language generalization
• Security and privacy of AI systems, including adversarial robustness and privacy-preserving LLM inference

Selected Publications

1. Sultan, M. F., Karim, T., Hossain Shaon, M. S., Wardat, M., and Akter, M. S. "CodeGraphNet: Embedding-Driven Enhanced Vulnerability Detection with Line Level Error Highlighting." Software Quality Journal, 2025. DOI: https://doi.org/10.1007/s11219-026-09752-9
2. Akter, M. S., Sultan, M. F., and Cuzzocrea, A. "Neuro-Symbolic Methods in Natural Language Processing: A Review." DATA 2025. DOI: https://doi.org/10.5220/0013453100003967
3. Karim, T., Akter, M. S., and Cuzzocrea, A. "A Benchmark Dataset for Code-Level Vulnerability Detection and Analysis." IEEE BigData 2025. DOI: https://doi.org/10.1109/BigData66926.2025.11402559
4. Hossain Shaon, M. S., Akter, M. S., and Cuzzocrea, A. "ResVul-LLM: A Neurosymbolic Framework Combining Large Language Models and Symbolic Reasoning for C/C++ Vulnerability Analysis." IEEE BigData 2025. DOI: https://doi.org/10.1109/BigData66926.2025.11402220
5. Sultan, M. F., Akter, M. S., and Cuzzocrea, A. "CodeVul+: A Structure-Aware Framework for Cross-Repository Vulnerability Detection." IEEE BigData 2025. DOI: https://doi.org/10.1109/BigData66926.2025.11401065
6. Sultan, M. F., Akter, M. S., and Cuzzocrea, A. "P3R: Parallel Plugin-based Parameter Efficient Fine-tuning for Code Understanding through Hierarchical Representation Refinement." IEEE BigData 2025. DOI: https://doi.org/10.1109/BigData66926.2025.11402539
7. Hossain Shaon, M. S., and Akter, M. S. "Modern Approaches to Software Vulnerability Detection: A Survey of Machine Learning, Deep Learning, and Large Language Models." Electronics, 2025. DOI: https://doi.org/10.3390/electronics14224449
8. Karim, T., and Akter, M. S. "Vulnerability Datasets for Software Security: A Survey of Existing Resources, Challenges, and Future Directions." Computers & Security, Elsevier, 2026. DOI: https://doi.org/10.1016/j.cose.2026.104926

Selected Grants and Funded Projects

NASA Michigan Space Grant Consortium Seed Grant (Funded): Efficient Neuro-Symbolic LLM-Driven Framework for Real-Time Detection and Mitigation of Software Vulnerabilities in Autonomous Spacecraft Systems; PI; $5,000 plus $5,000 Oakland University match; 2025.