Measuring and Analyzing Online Anonymous (Darknet) Marketplaces

Abstract

We propose to build on six years of research online anonymous ("darknet") marketplaces, in which we (i) designed and deployed collection infrastructure prototypes to rapidly and reliably acquire darknet marketplace data, and (ii) used this infrastructure to provide precise economic assessments of the size of darknet markets. Besides continued data collection, we plan on carrying out analyses at both the macro-level (i.e., over the entire ecosystem of marketplaces), and the micro-level (i.e., between vendors). At the macro-level, we are interested in longitudinal collection and analysis, so that we can better understand events both on short timescales (e.g., responses to takedowns, scams or other adversarial behavior), as well as longer time intervals (e.g., diversification or consolidation around certain markets). At the micro-level, we wish to develop methodologies and tools to understand how vendors are diversifying over time, or on the contrary, specializing; whether, and to which extent, mergers and acquisitions take place between vendors; to which extent arbitrage or brokerage occurs; whether vendors increasingly engage in operational security practices or not. Our proposed work consists of the following five tasks: 1) additional data collection and maintenance of our existing data collection infrastructure, 2) integration of collected, processed data into IMPACT, 3) macro-level longitudinal analysis of the ecosystem (including comparative analysis of the various activity sectors), 4) micro-level analysis of vendor strategies, and 5) transition of our frameworks and findings to practitioners, through a partnership with the National Cyber-Forensics Training Alliance (NCFTA).

Document Details

Document Type
DoD Grant Award
Publication Date
Jul 29, 2021
Source ID
FA87502011003

Entities

People

  • Nicolas Christin

Organizations

  • Carnegie Mellon University
  • Rome Laboratory
  • United States Air Force

Tags

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Economics
  • Industrial Economics

Technology Areas

  • Cyber