Please use this identifier to cite or link to this item: http://hdl.handle.net/10125/50005

XLab: Early Indications & Warnings from Open Source Data with Application to Biological Threat

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Title: XLab: Early Indications & Warnings from Open Source Data with Application to Biological Threat
Authors: Simek, Olga
Davis, Curtis
Heier, Andrew
Mohindra, Sanjeev
O'Brien, Kyle
show 2 morePassarelli, John
Waugh, Frederick

show less
Keywords: Decision Support for Complex Networks
indications and warnings, graph matching, threat models
Issue Date: 03 Jan 2018
Abstract: XLab is an early warning system that addresses a broad range of national security threats using a flexible, rapidly reconfigurable architecture. XLab enables intelligence analysts to visualize, explore, and query a knowledge base constructed from multiple data sources, guided by subject matter expertise codified in threat model graphs. This paper describes a novel system prototype that addresses threats arising from biological weapons of mass destruction. The prototype applies knowledge extraction analytics-”including link estimation, entity disambiguation, and event detection-”to build a knowledge base of 40 million entities and 140 million relationships from open sources. Exact and inexact subgraph matching analytics enable analysts to search the knowledge base for instances of modeled threats. The paper introduces new methods for inexact matching that accommodate threat models with temporal and geospatial patterns. System performance is demonstrated using several simplified threat models and an embedded scenario.
Pages/Duration: 10 pages
URI/DOI: http://hdl.handle.net/10125/50005
ISBN: 978-0-9981331-1-9
Rights: Attribution-NonCommercial-NoDerivatives 4.0 International
Appears in Collections:Decision Support for Complex Networks


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