Radhika Khandelwal
Papers
1
Total Citations
4
H-Index
1
About
Radhika Khandelwal’s research centers on cybersecurity, web analytics, and machine learning, with a particular focus on detecting and categorizing malicious automated agents—or web robots—that threaten internet security. Her most cited work, “Categorization Performance of Unsupervised Learning Techniques for Web Robots Sessions” (2018), tackles the challenge of identifying camouflaged bots in web server logs, which are often used for spamming, spying, or other harmful activities. By evaluating unsupervised learning methods, Khandelwal provides a foundational approach to distinguishing benign from malicious robot sessions, contributing to more robust web security frameworks. Though her citation count is still growing, this work has garnered attention for addressing a critical gap in bot detection. Her research is particularly valuable for students and practitioners in cybersecurity and data mining, offering practical insights into unsupervised classification techniques. Khandelwal’s efforts highlight the ongoing battle against automated threats, making her a promising voice in the field of web security and machine learning applications.
Research Focus
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Top Papers
- 1