Crowdsourcing Physical Network Topology Mapping With Net.Tagger

Abstract

Despite significant research, the challenge of mapping the physical topology of large networks remains a relatively unsolved problem. Although it possesses numerous ramifications for Internet security and resiliency, physical network geolocation research has not matched corresponding advancements made in logical topology mapping. This thesis proposes net.Tagger: a novel approach to network infrastructure mapping that combines smartphone apps with crowdsourced collection to gather data for offline aggregation and analysis. The project aims to build a map of physical network infrastructure such as fiber-optic cables, facilities, and access points. The net.Tagger project aligns to the OpenStreetMap project, a proven, open-source framework for managing crowd sourced map data. This thesis delivers a working proof-of-concept system for further research, including a smartphone app for gathering physical topology data, and the backend services to process and store it. We also present the results of an initial release to 25 users, analysing collection trends and extrapolating to predict potential findings of a future large-scale release.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2016
Accession Number
AD1027723

Entities

People

  • Daniel G. Woodman

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Biomedical
  • Cyber
  • Energy and Power Technologies
  • Engineered Resilient Systems
  • Materials and Manufacturing Processes
  • Sensors
  • Space

DTIC Thesaurus Topics

  • Commerce
  • Communication Systems
  • Computer Program Documentation
  • Computer Programming
  • Computer Science
  • Computers
  • Information Systems
  • Measurement
  • Mobile Application Software
  • Mobile Devices
  • Mobile Operating Systems
  • Mobile Phones
  • Network Protocols
  • Network Topology
  • Operating Systems
  • Relational Database Management Systems
  • Smartphones

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Computer Vision.
  • Distributed Systems and Data Platform Development