Emergency Monitoring via Encrypted Reverberation and Graph-based Environmental Detection of Anomalous Kinetic events (EMERGE-DARK)

Emergency Monitoring via Encrypted Reverberation and Graph-based Environmental Detection of Anomalous Kinetic events (EMERGE-DARK) | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Emergency Monitoring via Encrypted Reverberation and Graph-based Environmental Detection of Anomalous Kinetic events (EMERGE-DARK) Fazal Tariq, Muhammad Tufail, Fazal Tariq This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9189160/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Crises are growing more and more dependent on encrypted message platforms, which poses a severe blind spot to the old system of crisis monitoring. The proposed framework (EMERGE-DARK) presents here a privacy-preserving framework that detects emerging crises by analyzing the digital reverberations of private activities across observable data layers, identified public social media, search trends and network traffic without accessing protected communications. On the politically sensitive May 2023 crisis in Pakistan, our framework detected the emergency with 94% confidence 3 hours before widespread physical manifestations, identified Islamabad as the epicenter (33.9% probability) and maintained strong differential privacy guarantees ($\varepsilon=0.5$, $\delta=10^{-6}$). This work establishes a novel paradigm for ethically grounded emergency awareness in an age of encrypted communication, demonstrating that formal privacy protection and effective crisis detection can coexist through careful system design. Emergency Event Detection Dark Social Hybrid Analytics Inferential Modeling Big Data Machine Learning Ethics in AI Situational Awareness Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9189160","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":630560796,"identity":"200d980d-3596-457b-b010-d94ad0dbe205","order_by":0,"name":"Fazal Tariq","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+ElEQVRIiWNgGAWjYJCCD0AsA2IcYKgAkszMDYR0MM4AEjw8YC1nQFoYSdDCwNgGJvFrMZc+fLDhxx87Hnv2sw8PvJ1XG83fDtTyo2IbTi2WfWmJjT08yTw8POkGB+duO5474zBjA2PPmds4tRic4TF/wCPBDHRYGsNh3m3HchuAWpgZ2/BqMWz8Y1DPw8P/DKhlzrHc+cRoaeZJOMzDIwGypaEmdwMhLZY9bInNMgeO8/DceMZwcM6xA7kbgVoO4vOLOQ/zwcY3f6rl2PvTmD+8qanLnXf+8MEHPyrwOAyFx8NwGEwfwKkei5Y6fIpHwSgYBaNghAIAkXVZnS7gnQ8AAAAASUVORK5CYII=","orcid":"","institution":"Govt. 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