Mitigating Aggressive Crawler Traffic in the Age of Generative AI: A Collaborative Approach from the University of North Carolina at Chapel Hill Libraries

The rise of aggressive, adaptive, and evasive web crawlers is a significant challenge for libraries and archives, causing service disruptions and overwhelming institutional resources. This article details the experiences of the University of North Carolina at Chapel Hill University Libraries in combating an unprecedented flood of crawler traffic. It describes the escalating mitigation efforts, from traditional client blocking to the implementation of more advanced techniques such as request throttling, regional traffic prioritization, novel facet-based bot detection, commercial Web Application Firewalls (WAFs), and ultimately, in-browser client verification with Cloudflare Turnstile. The article highlights the adaptive nature of these crawlers, the limitations of isolated institutional responses, and the critical lessons learned from mitigation efforts, including the issues introduced by residential proxy networks and the extreme scale of the traffic. Our experiences demonstrate the effectiveness of a multi-layered defense strategy that includes both commercial and library-specific solutions, such as facet-based bot detection. The article emphasizes the importance of community-wide collaboration, proposing future directions such as formalized knowledge sharing and the ongoing development of best practices to collectively address this evolving threat to open access and the stability of digital library services.

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Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2025-10-01
Primary Topic
Web Data Mining and Analysis
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article
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article

Mitigating Aggressive Crawler Traffic in the Age of Generative AI: A Collaborative Approach from the University of North Carolina at Chapel Hill Libraries

David Romani, Tim Shearer, Jason Casden, Jeff Campbell
SHILAP Revista de lepidopterología
Web Data Mining and Analysis
article

Mitigating Aggressive Crawler Traffic in the Age of Generative AI: A Collaborative Approach from the University of North Carolina at Chapel Hill Libraries

David Romani, Tim Shearer, Jason Casden, Jeff Campbell
article en

Abstract

The rise of aggressive, adaptive, and evasive web crawlers is a significant challenge for libraries and archives, causing service disruptions and overwhelming institutional resources. This article details the experiences of the University of North Carolina at Chapel Hill University Libraries in combating an unprecedented flood of crawler traffic. It describes the escalating mitigation efforts, from traditional client blocking to the implementation of more advanced techniques such as request throttling, regional traffic prioritization, novel facet-based bot detection, commercial Web Application Firewalls (WAFs), and ultimately, in-browser client verification with Cloudflare Turnstile. The article highlights the adaptive nature of these crawlers, the limitations of isolated institutional responses, and the critical lessons learned from mitigation efforts, including the issues introduced by residential proxy networks and the extreme scale of the traffic. Our experiences demonstrate the effectiveness of a multi-layered defense strategy that includes both commercial and library-specific solutions, such as facet-based bot detection. The article emphasizes the importance of community-wide collaboration, proposing future directions such as formalized knowledge sharing and the ongoing development of best practices to collectively address this evolving threat to open access and the stability of digital library services.

SHILAP Revista de lepidopterología
Openalex Percentile: Top 19%
Web Data Mining and Analysis
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