Reza Sadeghi

Wright State University, Imam Reza International University

Papers

Total Citations

H-Index

About

Dr. Reza Sadeghi is a leading researcher in cybersecurity and web intelligence, with a focus on distinguishing benign web traffic from malicious automated threats. His work centers on developing soft computing and fuzzy rough set methodologies to detect web robots—both helpful crawlers and harmful bots—with high accuracy. In his most-cited paper, "A soft computing approach for benign and malicious web robot detection" (2017, 42 citations), he introduced a novel framework that leverages fuzzy logic to handle the uncertainty inherent in web visitor behavior, achieving superior classification performance. Expanding on this, his study "Detection of Web site visitors based on fuzzy rough sets" (2017, 37 citations) further refined detection by integrating rough set theory to reduce feature redundancy and improve interpretability. These contributions have practical implications for enhancing web security, protecting against data scraping, and optimizing server resources. Dr. Sadeghi’s work is widely recognized for bridging computational intelligence and cybersecurity, offering robust, adaptive solutions for real-time bot detection. His research continues to influence both academic studies and industry applications, making him a key figure in the evolving landscape of web threat analysis.