Rahimi Samaneh
Papers
1
Total Citations
4
H-Index
1
About
Rahimi Samaneh is a researcher whose work sits at the intersection of cybersecurity, data mining, and fuzzy rough set theory. Her most notable contribution, the paper "FRS-SIFS: fuzzy rough set session identification and feature selection in web robot detection" (2023), introduces a novel framework that leverages fuzzy rough sets to enhance the detection of malicious web robots. By improving session identification and feature selection, this work addresses critical challenges in distinguishing human users from automated bots, a growing concern in web security. With 4 citations already, this paper signals early impact in a niche but vital area. Samaneh’s research is particularly valuable for its integration of computational intelligence techniques with practical cybersecurity applications, offering a robust method for reducing false positives in bot detection. Her work stands out for its methodological rigor and potential to strengthen online security systems, making her a promising voice in the evolving field of intelligent web defense.
Research Focus
Key Achievements
Top Papers
- 1