Athena Stassopoulou

Papers

Total Citations

160

H-Index

About

Athena Stassopoulou is a leading researcher in web intelligence and probabilistic modeling, best known for her pioneering work in web robot and crawler detection. Her research focuses on developing probabilistic reasoning frameworks to distinguish automated web crawlers from human users, a critical challenge for web security and analytics. Her most influential contribution is the 2008 paper "Web robot detection: A probabilistic reasoning approach," which has garnered 101 citations and established a foundational methodology for identifying crawler behavior from web-server access logs. Stassopoulou introduced Bayesian network classifiers that automatically categorize access-log sessions as either crawler- or human-induced, significantly improving detection accuracy over traditional rule-based methods. Her earlier works, including "Crawler Detection: A Bayesian Approach" (21 citations) and "Characterizing Crawler Behavior from Web Server Access Logs" (20 citations), further refined these techniques by analyzing crawler behavioral patterns. Her 2007 paper on discovering web crawler sessions (18 citations) extended probabilistic reasoning to session-level analysis. Collectively, her research has shaped modern approaches to web robot detection, with applications in cybersecurity, web analytics, and server resource management. Stassopoulou's work remains highly cited for its rigorous probabilistic foundations and practical relevance to evolving web environments.