Alexander Menshchikov

Papers

Total Citations

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About

Alexander Menshchikov is a researcher specializing in web robotics, web crawling behavior, and cybersecurity detection methods. His work focuses on understanding how automated web crawlers and scrapers interact with web servers, and developing techniques to identify and classify them. In his most cited paper, "A study of different web-crawler behaviour" (2017, 9 citations), Menshchikov provides a comprehensive classification of web robots and information gathering tools, analyzing their behavior using large-scale web server logs. This foundational work has been instrumental for researchers developing detection methods against malicious scraping. His subsequent study, "Modeling the behavior of web crawlers on a web resource" (2020, 2 citations), introduces a simulation model for web crawler behavior, enabling improved detection techniques and dataset generation for machine learning approaches. Menshchikov's contributions are particularly valuable for web administrators and cybersecurity professionals seeking to protect web resources from unauthorized data extraction, while also informing the design of legitimate web crawlers. His work bridges the gap between theoretical modeling and practical detection, making him a notable figure in web robot research.