Redefining Attack: Taking the Offensive Against Networks

Abstract

The Information Age empowers individuals, and affords small groups an opportunity to attack states' interests with an increasing variety of tactics and great anonymity. Current strategies to prevail against these emerging threats are inherently defensive, relying on potential adversaries to commit mistakes and engage in detectable behavior. While defensive strategies are a critical component of a complete solution set, they cede initiative to the adversary. Moreover, reactive measures are not suited to quickly suppress adversary networks through force. To address this shortfall in strategic planning, the science of networks is rapidly making clear that natural systems built over time with preferential attachment form scale-free networks. These networks are naturally resilient to failure and random attack, but carry inherent vulnerabilities in their highly connected hubs. Taking the offensive against networks is therefore an exercise in discovering and attacking such hubs. To find these hub vulnerabilities in network adversaries, this thesis proposes a strategy called Stimulus Based Discovery, which leads to rapid network mapping and then systematically improves the accuracy and validity of this map while simultaneously degrading an adversary's network cohesion. Additionally, this thesis provides a model for experimenting with Stimulus Based Discovery in a Multi-Agent System.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2003
Accession Number
ADA415027

Entities

People

  • Robert J. Michael Ii
  • Zachary H. Staples

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Autonomy
  • Cyber
  • Energy and Power Technologies
  • Ground and Sea Platforms
  • Space

DTIC Thesaurus Topics

  • Computers
  • Contingency Operations (Military)
  • Human Behavior
  • Information Systems
  • International Law
  • International Relations
  • Military History
  • Military Organizations
  • Military Science
  • Multiagent Systems
  • National Security
  • Network Science
  • Students
  • Terrorism
  • Terrorists
  • Treaties
  • Warfare

Fields of Study

  • Computer science

Readers

  • Distributed Systems and Data Platform Development
  • Irregular Warfare and Special Operations Cyberspace Operations against Adversarial Threats.
  • Neural Network Machine Learning.