• Skip to primary navigation
  • Skip to main content

CINA.

  • About
    • Mission
    • People
  • Research
    • Research
    • Projects
    • RFPs
  • Education
    • Resources
    • Internships
  • Publications
    • Newsletter Archive
    • Director’s Blog
  • News & Events
    • News
    • CINA Director’s Blog
    • Digital Archive
    • Events
    • Work with Us
  • Contact
  • Search Toggle
  • Skip to content

Location Data Analytics and Visualization for Criminal Network Identification

Summary

Existing data analysis tools do not provide the visualization capabilities forensic analysts and investigators need to handle the huge amount of digital trace information generated by mobile devices and associated location data. Analysts need visualization tools that quickly help them get as much usable information as possible out of the available location data. This project will result in a set of layout algorithms and software packages that display location data in a way that allows investigators to identify potentially unusual and criminal activities.

 

Problem addressed

Geographic location data is recorded by the ubiquitous mobile phones in large amounts, potentially enabling investigators to paint a detailed picture of a suspect’s activities. However, the challenge they face today is one of data overload, and finding the golden needle in the haystack of location records is not sufficiently supported by existing methods and tools. An additional challenge lies in the fact that due to the changing nature of agents’ activities, some of these analyses may need to be done in the field, often on mobile devices, exacerbating the display and interactions challenges.

 

Approach

The goal of the proposed work is to develop and extend visualization and analytics tools that have been previously developed to enable analysts to more effectively analyze, understand, and benefit from location-based data. The key lies in intelligent algorithms to simplify and semi-automatically filter the data as well as in more compact visualization approaches that can provide a faster overview and better understanding of the target’s activities and patterns-of-life. The researchers will address issues of accuracy using statistical and plausibility approaches, then will present the data using clustering, visualization, and interaction algorithms to facilitate understanding of the data while avoiding data overload.

 

Anticipated Impact for DHS

The end result of the proposed work will be visualization components (software and algorithms) that integrate into other DHS and LE desktop and mobile applications and enable them to effectively handle large amounts of location-based information. The final goal is to provide analysts with a tool that helps them get as much usable information as possible out of the available location data in a short amount of time.

Topics:

  • Geospatial
  • Innovation and Technology
  • Networks

Research Areas:

  • Criminal network analysis
  • Network analytics

Investigators

  • Dirk Reiners
  • Carolina Cruz-Neira

*The programs and services offered by George Mason University are open to all who seek them. George Mason does not discriminate on the basis of race, color, religion, ethnic national origin (including shared ancestry and/or ethnic characteristics), sex, disability, military status (including veteran status), sexual orientation, gender identity, gender expression, age, marital status, pregnancy status, genetic information, or any other characteristic protected by law. After an initial review of its policies and practices, the university affirms its commitment to meet all federal mandates as articulated in federal law, as well as recent executive orders and federal agency directives.

CINA Now

Events

All Events

Publications

The Key to Deobfuscation is Pattern of Life, not Overcoming Encryption

Published: Oct 4, 2025

The Organized Activities of Ransomware Groups: A Social network Approach

Published: Mar 14, 2025
All Publications

News

CINA Distinguished Speaker Series with Colton Seale: Interviewer Mindset

CINA  |   April 3, 2025  |   Posted In:
  • Digital Archive
  • Uncategorized

CINA  |   March 6, 2025  |   Posted In:
  • Uncategorized
All News

Science and Technology Directorate’s Office of University Programs
CINA at George Mason University Logo
Copyright © 2025 All Rights Reserved | CINA Is A Department of Homeland Security Center of Excellence led by George Mason University
  • Facebook
  • Twitter
  • Instagram
  • Linkedin
  • YouTube