zabihimayvan
Link
Associate Professor
Computer Science
Cybersecurity, BS
Contact
(860) 832-2716
zabihimayvan@ccsu.edu
Office
Maria Sanford Hall
303
Biography

I work on the applications of artificial intelligence for cybersecurity with the aim of improving proactive cyber threat intelligence applications in protecting privacy of Internet users. I am particularly interested in applied machine learning and characterization, measurements, and analytics for complex cyber-security and socio-technical systems.

Please visit my page on https://sites.google.com/view/mzabihi for more info.

Areas of Expertise

Machine learning for Cybersecurity

Complex systems analysis

 

Publications, Research & Presentations
  1. Mahdavi, N., Sadeghi, R., Daliri, A., Zabihimayvan, M., Alimoradi, M., & Knapp, G. (2026). Cardiac arrhythmia detection via PQRST analyzed data using an optimized hierarchical fused fuzzy deep reinforcement learning. BMC Medical Informatics and Decision Making.
  2. Sadeghi, R., Bullock, L., Burian, L., Farina, R., & Pourkavoos, K. (2026). Excessive daytime sleepiness prevention using causality network driven by score-based Bayesian network structure learning algorithms. Smart Health, 100655.
  3. Daliri, A., Mahdavi, N., Zabihimayvan, M., Baranghar, A. N., & Zaeimzadeh, N. (2025). Reinforcement learning based deep fuzzy hierarchical clustering to generate personalized non-fungible token artwork. Neurocomputing, 131821.
  4. Mahdavi, N., Daliri, A., Zabihimayvan, M., Yaghooti, Y., Mir, M. M., & Ghazanfari, P. (2025). WHFDL: An explainable method based on World Hyper-heuristic and Fuzzy Deep Learning approaches for gastric cancer detection using metabolomics data. BioData Mining, 18(1), 72.
  5. Amin, F., Shaban, A., & Zabihimayvan, M. (2025). Comparative analysis of machine learning models for phishing detection: Leveraging textual and numerical data from URLs. In Intelligent Systems Conference (pp. 646–657).
  6. Alimoradi, M., Sadeghi, R., Daliri, A., & Zabihimayvan, M. (2025). Statistic deviation mode balancer (SDMB): A novel sampling algorithm for imbalanced data. Neurocomputing, 624, 129484.
  7. Zabihimayvan, M., Sadeghi, R., & Doran, D. (2024). Security, information, and structure characterization of Tor: A survey. Telecommunication Systems, 87(1).
  8. Daliri, A., Alimoradi, M., Zabihimayvan, M., & Sadeghi, R. (2024). World Hyper-Heuristic: A novel reinforcement learning approach for dynamic exploration and exploitation. Expert Systems with Applications, 244, 122931.
  9. Daliri, A., Khoshbakhti, M., Samadi, M. K., Rahiminia, M., & Zabihimayvan, M. (2024). Equilateral Active Learning (EAL): A novel framework for predicting autism spectrum disorder based on active fuzzy federated learning. In Artificial Intelligence and Social Computing.
  10. Daliri, A., Zabihimayvan, M., & Saleh, K. (2024). Vector Result Rate (VRR): A novel method for fraud detection in mobile payment systems. In Artificial Intelligence and Social Computing (Vol. 122, pp. 52–61).
  11. McConnell, B., Del Monaco, D., Zabihimayvan, M., & Abdollahzadeh, F. (2023). Phishing attack detection: An improved performance through ensemble learning. In International Conference on Artificial Intelligence and Soft Computing (pp. 145–157).
  12. Zabihimayvan, M., & Doran, D. (2022). A first look at references from the dark to the surface web world: A case study in Tor. International Journal of Information Security, 21(4), 739–755.
  13. Sledzik, R., & Zabihimayvan, M. (2022). Focal loss improves performance of high-sensitivity c-reactive protein imbalanced classification. In 2022 IEEE 35th International Symposium on Computer-Based Medical Systems (CBMS).
  14. Alimoradi, M., Zabihimayvan, M., Daliri, A., Sledzik, R., & Sadeghi, R. (2022). Deep neural classification of darknet traffic. In Artificial Intelligence Research and Development (pp. 105–114).
  15. Zabihimayvan, M., Sadeghi, R., Kadariya, D., & Doran, D. (2020). Interaction of structure and information on Tor. In International Conference on Complex Networks and Their Applications (pp. 296–307).
  16. Romine, W. L., Schroeder, N. L., Graft, J., Yang, F., Sadeghi, R., Zabihimayvan, M., & Banerjee, T. (2020). Using machine learning to train a wearable device for measuring students’ cognitive load during problem-solving activities based on electrodermal activity, body temperature. Sensors, 20(17), 4833.
  17. Zabihimayvan, M. (2020). New perspectives about the Tor ecosystem: Integrating structure with information (Doctoral dissertation / Master's thesis, Wright State University).
  18. Zabihimayvan, M., & Doran, D. (2019). A first look at references from the dark to surface web world. arXiv preprint arXiv:1911.07814.
  19. Zabihimayvan, M., & Doran, D. (2019). Fuzzy rough set feature selection to enhance phishing attack detection. arXiv preprint arXiv:1903.05675.
  20. Zabihimayvan, M., Sadeghi, R., Doran, D., & Allahyari, M. (2019). A broad evaluation of the Tor English content ecosystem. In Proceedings of the 11th ACM Conference on Web Science (pp. 333–342).
  21. Hamidzadeh, J., Zabihimayvan, M., & Sadeghi, R. (2018). Detection of Web site visitors based on fuzzy rough sets. Soft Computing, 22(7), 2175–2188.
  22. Zabihimayvan, M., & Doran, D. (2018). Some (non-) universal features of web robot traffic. In 2018 52nd Annual Conference on Information Sciences and Systems (CISS) (pp. 1–6).
  23. Zabihimayvan, M., Sadeghi, R., Rude, H. N., & Doran, D. (2017). A soft computing approach for benign and malicious web robot detection. Expert Systems with Applications, 87, 129–140.
  24. Zabihi, M., Jahan, M. V., & Hamidzadeh, J. (2014). A density based clustering approach for web robot detection. In 2014 4th International Conference on Computer and Knowledge Engineering (ICCKE).
  25. Zabihi, M., Jahan, M. V., & Hamidzadeh, J. (2014). ISeCure. In 2014 International Conference on Computer and Knowledge Engineering.
Awards & Grants

• Next Generation of Student Success, Diversity, Innovation and Community Engagement Grant Competition, 2024-26 

• David Educational Foundation Grant, CCSU, March2023-December 2023 

• AAUP Faculty Development Grant, August 2022-August 2023 

• CSU-AAUP University Faculty Research Grant, CCSU, September 2022-September 2023 

• SEST Faculty Research Fellowship Award, School of Engineering, Science and Technology, CCSU, August 2021-July 2022 

• Travel Grant, The 53rd ACM Technical Symposium on Computer Science Education, Providence, Rhoad Island, March 2022

Memberships & Affiliations
  • European Society for Fuzzy Logic and Technology
  • ACM-W
  • Women in Network Science
  • Women in Machine Learning
  • WomenTech Network
Courses Taught
  • CS 446/546- ML for Cybersecurity, Fall 2025, Summer 2026
  • CS/CYS 492- Computer Security, Spring 2022-2023
  • CS/CYS 455- Secure Software Development, Spring 2023
  • CS 430/580- Big Data Programming, Fall 2021
  • CS 355- Systems Programming, Spring 2021-2023
  • CS/CYS 493/560- Secure Software Designs, Fall 2020-2022
  • CS 110- Introduction to Internet Programming, Fall 2020