Economic Modeling of a Trust Network via Positive Collusion and Aspiration Adaptation

Abstract

Military communities in tactical networks must often maintain high group solidarity based on the trustworthiness of participating individual entities where collaboration is critical to performing team-oriented missions. Group trust is regarded as more important than trust of an individual entity since consensus among or compliance of participating entities with given protocols may significantly affect successful mission completion. This work introduces a game theoretic approach, namely Aoyagis game theory on collusion in a dynamic Bertrand oligopoly. This approach improves group trust by using positive collusion encouraging unanimous compliance with a given group protocol. Further, inspired by aspiration theory in social sciences, we adjust the expected system trust threshold level that should be maintained by all participating entities to effectively encourage benign behaviors. The results show that there exist optimal settings (e.g., system trust threshold level) that can maximize group trust level while meeting required system lifetime (survivability).

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Document Details

Document Type
Technical Report
Publication Date
Oct 28, 2010
Accession Number
AD1004681

Entities

People

  • Ananthram Swami
  • Jin-Hee Cho

Organizations

  • United States Army Research Laboratory

Tags

Communities of Interest

  • Cyber

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Cellular Networks
  • Computer Science
  • Computers
  • Detectors
  • Game Theory
  • Intrusion Detection
  • Intrusion Detection Systems
  • Intrusion Detectors
  • Mathematical Models
  • Mobile Phones
  • Models
  • Networks
  • Probability
  • Sensor Networks
  • Survivability
  • Tactical Networks

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Computer Networking
  • Organizational Psychology.

Technology Areas

  • Fully Networked C3
  • Fully Networked C3 - Command and Control