Mahdieh Zabihimayvan

Wright State University, Imam Reza International University, Central Connecticut State University

Papers

Total Citations

H-Index

About

Dr. Mahdieh Zabihimayvan is a leading researcher in web security and intelligent systems, whose work has fundamentally advanced the detection and characterization of automated web traffic. Her research centers on developing soft computing and machine learning frameworks to distinguish benign web robots from malicious automated scripts, a critical challenge for modern cybersecurity. Dr. Zabihimayvan’s most influential contribution is her pioneering application of fuzzy rough set theory for web robot detection, a methodology that has garnered significant attention with her 2017 paper on the topic receiving 37 citations. Her landmark study, “A soft computing approach for benign and malicious web robot detection,” has been cited 42 times, establishing a new paradigm for handling the uncertainty inherent in web traffic classification. Beyond detection, her work on the universal features of web robot traffic—based on extensive analysis of three U.S. and European web servers—provides essential insights for mitigating the impact of automated traffic on web infrastructure. Her most recent 2024 evaluation of machine learning techniques continues to shape the field, offering updated benchmarks for practitioners. Dr. Zabihimayvan’s research remains indispensable for anyone seeking to understand and defend against the evolving landscape of web automation.