I am a Ph.D. candidate of the Department of Computer Science and Engineering at University of Colorado Denver. Currently, I am a member of Active Cyber and Infrastructure Defense (ACID) laboratory under the supervision of Dr. Haadi Jafarian. My research interests encompass a wide range of topics, mostly in the field of Cybersecurity and Data Science, but not limited to Security and Privacy, and Network Traffic Analysis. I am also quite interested in other fields of Computer Science such as Software-Defined Networks, Cryptography, and Internet of Things, etc. I received my B.Sc. and M.Sc. from University of Tehran and Tehran polytechnic University respectively.
My primary research interests include:
Data-driven Cybersecurity
Privacy-enhancing Technologies
Network Traffic Analysis
Big Data Analytics for Cyber Threat Intelligence
Machine Learning
Deep Learning
Toward Enhancing Web Privacy on Https Traffic: A Novel Superlearner Attack Model and an Efficient Defense Approach with Adversarial Examples, M Abolfathi, S Inturi, F Banaei-Kashani, JH Jafarian. Computers and Security 2023
Attack Detection Analysis in Software-defined Networks using Various Machine Learning Method, Wang, Y., Wang, X., Ariffin, M., Abolfathi, M., Alqhatani, A., Almutairi, L. Computers and Electrical Engineering 2023
Detecting Network Scanning Through Monitoring and Manipulation of DNS Traffic, Jafarian, H., Abolfathi, M., Rahimian, M. IEEE Access 2023
A Game-Theoretically Optimal Defense Paradigm against Traffic Analysis Attacks using Multipath Routing and Deception, Abolfathi, M., Shomorony, I., Vahid, A., & Jafarian, H. Proceedings of the ACM SACMAT 2022
Practical Black Box Model Inversion Attacks against Neural Nets, Bekman, T., Abolfathi. M., Jafarian. H., Biswas. A., Banaei-Kashani. F., & Das, K., MLCS/ECML-PKDD 2021
An Accurate and Scalable Role Mining Algorithm based on Graph Embedding and Unsupervised Feature Learning, Masoumeh Abolfathi, Zohreh Raghebi, J. Haadi Jafarian, Farnoush Banaei-Kashani, Hawaii International Conference on System Sciences, 2020.
A Scalable Role Mining Approach for Large Organizations, Abolfathi, M., Raghebi, Z., Jafarian, H., & Banaei-kashani, F., IWSPA 2021.