Evaluation of Network Trust Using Provenance Based on Distributed Local Intelligence

Abstract

Provenance can play a significant role in a military information system for supporting the calculation of information trust. A nodes trust can change over time after its initial deployment due to various reasons such as energy loss, environmental conditions or exhausting sources. We introduce a node-level trust-enhancing mechanism for information networks using provenance. A unique characteristic of the proposed trust architecture presented here is the use of provenance through the path of the information from source to destination in determining the information trust. In this proposed architecture each node in the system has a trust and provenance vector. Each information item transmitted over the network has a trust value associated with it. Nodes reexamine and update the trust value associated with the information, creating a distributed system that is more flexible and more responsive. As our system allows reconfigurations, initiatives taken by the intermediate nodes such as replacement of untrusted nodes will enhance the network trust in mission critical situations faster than a centralized approach.

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Document Details

Document Type
Technical Report
Publication Date
Nov 07, 2011
Accession Number
AD1004688

Entities

People

  • Gulustan Dogan
  • Jin-Hee Cho
  • Kannan Govindan
  • Mohammad M. Khan
  • Prasant Mohapatra
  • Tarek Abdelzaher
  • Theodore Brown

Organizations

  • United States Army Research Laboratory

Tags

Communities of Interest

  • Energy and Power Technologies
  • Sensors

DTIC Thesaurus Topics

  • Accuracy
  • Algorithms
  • Automotive Industry
  • Computations
  • Databases
  • Detection
  • Detectors
  • Digital Information
  • Energy Consumption
  • Energy Efficiency
  • Military Research
  • Networks
  • Sensor Networks
  • Standards
  • Time Intervals
  • Wireless Networks
  • Wireless Sensor Networks

Fields of Study

  • Computer science

Readers

  • Computer Networking
  • Cybersecurity.
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.