Javad Hamidzadeh

Papers

Total Citations

H-Index

About

Javad Hamidzadeh is a researcher specializing in cybersecurity, web robot detection, and fuzzy rough set theory. His work focuses on distinguishing human users from automated web robots to enhance network security and server performance. His most cited paper, "Detection of Web site visitors based on fuzzy rough sets" (2017, 37 citations), introduces a novel approach using fuzzy rough sets to identify malicious web traffic. Another influential work, "A density based clustering approach for web robot detection" (2014, 18 citations), proposes a clustering method to differentiate humans from robots, addressing a critical challenge in computer network security. More recently, Hamidzadeh developed "FRS-SIFS: fuzzy rough set session identification and feature selection in web robot detection" (2023, 4 citations), refining session identification and feature selection techniques. His contributions have practical implications for protecting websites from intrusion and improving server efficiency by prioritizing human users. With a cumulative citation impact exceeding 60, Hamidzadeh’s research advances the intersection of fuzzy logic, data mining, and cybersecurity, offering robust solutions for real-world web security challenges.