Search signals that guide censorship investigation
CenAlert · IEEE Symposium on Security and Privacy (S&P), 2026
By Aaron Ortwein, Anna Ablove, Armin Huremagic, Luqin Chang, Vinicius Fortuna, and Roya Ensafi.
The question
Can people’s searches for circumvention tools help researchers find events that need closer investigation?
The contribution
CenAlert examines increases in Google Trends search interest and uses them to help prioritize investigation of possible censorship events. The work includes an open-source system, dashboard, and integration interfaces.
Abstract
The commoditization of deep packet inspection technology has eased the deployment of Internet censorship, even in countries typically considered open. While the Internet freedom community has been vital to increasing transparency, its coverage relies heavily on NGOs and activists, whose ability to relay user reports of censorship is increasingly threatened by mounting risks, anti-NGO legislation, and foreign funding cuts. To bridge this widening gap, we examine whether other data sources can be repurposed to amplify user voices and rally censorship investigation. We leverage Google Trends data to build CenAlert, a user-driven alert system that detects spikes in search interest for circumvention tools. Each spike is scored with an impact factor quantifying increases in circumvention tool demand and enabling prioritization of response efforts. We demonstrate the effectiveness and practicality of CenAlert across 76 censoring countries over 14 years. Of 269 selected spikes, 191 are explainable, including 153 as censorship events. Notably, 68 spikes correspond to censorship events not previously reported by the community. To facilitate integration with observatories, CenAlert is open-source and provides a dashboard, API, and Slack webhook for notification, visualization, and analysis of potential censorship events. Ultimately, CenAlert offers a novel solution to long-standing challenges faced by the Internet freedom community.