Threat Network Detection and Tracking

Abstract

Identifying and profiling threat actors arehigh priority tasks for a number of governmental organizations. These threat actors may operateactively, using the Internet to promote propaganda, recruit new members, or exert command and controlover their networks. Alternatively, threat actors may operate passively, demonstrating operational security awareness online while using their Internet presence togather information they need to pose an offline physical threat. This paper presents a flexible new prototype that allows analysts to automatically detect, monitor and characterize threat actors and their networks using publicly available information. It fills a need in the intelligence community for a capability to automate manual construction and analysis of online threat networks.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Oct 22, 2018
Accession Number
AD1120360

Entities

People

  • Andrew Heier
  • Danelle Shah
  • John Passarelli
  • Olga Simek

Organizations

  • MIT Lincoln Laboratory

Tags

Communities of Interest

  • Autonomy
  • C4I

DTIC Thesaurus Topics

  • Computational Science
  • Department Of Defense
  • Detection
  • Language
  • Machine Learning
  • Media
  • Natural Language Processing
  • Natural Languages
  • Neural Networks
  • Online Communications
  • Social Media
  • Social Networking Services
  • Social Networks
  • Social Sciences
  • Supervised Machine Learning
  • Terrorism
  • Terrorists

Fields of Study

  • Computer science

Readers

  • Distributed Systems and Data Platform Development
  • Irregular Warfare and Special Operations Cyberspace Operations against Adversarial Threats.
  • Sensor Fusion and Tracking Systems.