Wireless Emergency Alerts: Trust Model Technical Report

Abstract

Trust is a key factor in the effectiveness of the Wireless Emergency Alerts (WEA) service. Alert originators (AOs) must trust WEA to deliver alerts to the public in an accurate and timely manner. Members of the public must also trust the WEA service before they will act on the alerts that they receive. This research aimed to develop a trust model to enable the Federal Emergency Management Agency (FEMA) to maximize the effectiveness of WEA and provide guidance for AOs that would support them in using WEA in a manner that maximizes public safety. The research method included Bayesian belief networks to model trust in WEA because they enable reasoning about and modeling of uncertainty. The research approach was to build models that could predict the levels of AO trust and public trust in specific scenarios, validate these models using data collected from AOs and the public, and execute simulations on these models for numerous scenarios to identify recommendations to AOs and FEMA for actions to take that increase trust and actions to avoid that decrease trust. This report describes the process used to develop and validate the trust models and the resulting structure and functionality of the models.

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Document Details

Document Type
Technical Report
Publication Date
Feb 01, 2014
Accession Number
ADA610097

Entities

People

  • Jim Mccurley
  • Joseph P. Elm
  • Robert W. Stoddard Ii
  • Sarah Sheard
  • Tamara Marshall-keim

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Cyber
  • Energy and Power Technologies
  • Engineered Resilient Systems
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Computational Science
  • Databases
  • Department Of Homeland Security
  • Emergency Response
  • Failure Mode And Effect Analysis
  • Geographic Regions
  • Information Science
  • Mobile Communications
  • Mobile Phones
  • National Governments
  • Public Administration
  • Smartphones
  • Social Media
  • Surveys
  • Text Messaging
  • United States Government
  • Warning Systems

Fields of Study

  • Computer science

Readers

  • Emergency Management and Homeland Security.
  • Fault Tolerant Diagnosis of Black and White Balloon Isolation Tests Using ¥.
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - DoD AI Strategy