Antonina Komarova

Papers

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About

Antonina Komarova is a researcher focused on the critical intersection of web data extraction and cybersecurity, with a primary emphasis on the behavior and detection of web crawlers. Her work provides foundational insights into how automated programs—from benign search engine bots to malicious scrapers—interact with web resources. In her highly cited 2017 study, Komarova conducted a comprehensive classification of web-robots and information gathering tools, analyzing their behavior against a large set of web-server logs to develop effective detection methods. This work, which has garnered 9 citations, established a practical taxonomy for understanding different crawler types. Building on this, her 2020 research introduced a simulation model of web-crawler behavior, a crucial tool for generating realistic datasets needed to train machine learning-based detection systems. By modeling the nuanced differences in how various crawlers operate, Komarova’s contributions are directly applicable to improving web server security and data integrity, offering both theoretical frameworks and practical methodologies for researchers and engineers working to protect online resources from unwanted automated access.