Namrata Verma
Papers
2
Total Citations
6
H-Index
2
About
Namrata Verma’s research focuses on cybersecurity and web traffic analysis, with a particular emphasis on detecting and mitigating malicious automated web activity. Her work addresses critical vulnerabilities in application-layer security, specifically targeting HTTP flood attacks and web robot (crawler) sessions that can overwhelm server resources and disrupt services. In her 2018 paper “Framework for Preprocessing and Feature Extraction from Weblogs for Identification of HTTP Flood Request Attacks,” she developed a systematic approach to identify distributed denial-of-service (DDoS) attacks at the application layer, a notoriously difficult area of defense. Her complementary study, “Performance Evaluation of Density-Based Clustering Methods for Categorizing Web Robot Sessions,” provides a comparative analysis of clustering techniques to distinguish legitimate human traffic from automated scripts, offering practical tools for server-side protection. Though her most-cited works each hold 3 citations, their impact lies in addressing a persistent and evolving threat in web security. Verma’s contributions are particularly valuable for researchers and practitioners working on intrusion detection, web log mining, and server resource management, providing foundational methodologies for identifying and classifying anomalous web traffic patterns.
Research Focus
Key Achievements
Top Papers
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