Augmenting Effectiveness of Threat Modeling through Threat Intelligence Attributes

Abstract

We propose a threat intelligence-driven modeling framework anchored on four enabling technologies: (1) open source threat intelligence; (2) big data; (3) artificial intelligence (AI); and (4) knowledge/rule base. Conveniently called TIME (threat intelligence modeling environment), it has continuous cycles of: (1) collect asset data; (2) gather vulnerability data; (3) agglomerate threat data; (4) correlate vulnerabilities and threats with assets; (5) derive threat intelligence and interpret its effects on assets; and (6) share threat intelligence with the community.

Document Details

Document Type
DoD Grant Award
Publication Date
Oct 09, 2018
Source ID
N001741710010

Entities

People

  • Bongsik Shin

Organizations

  • Salk Institute for Biological Studies
  • United States Navy

Tags

Fields of Study

  • Computer science

Readers

  • Distributed Systems and Data Platform Development
  • Geospatial Intelligence and Artificial Intelligence Analytics
  • Irregular Warfare and Special Operations Cyberspace Operations against Adversarial Threats.

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy