The responsiveness of criminal networks to intentional attacks: Disrupting darknet drug trade

PLoS One. 2020 Sep 10;15(9):e0238019. doi: 10.1371/journal.pone.0238019. eCollection 2020.

Abstract

Physical, technological, and social networks are often at risk of intentional attack. Despite the wide-spanning importance of network vulnerability, very little is known about how criminal networks respond to attacks or whether intentional attacks affect criminal activity in the long-run. To assess criminal network responsiveness, we designed an empirically-grounded agent-based simulation using population-level network data on 16,847 illicit drug exchanges between 7,295 users of an active darknet drug market and statistical methods for simulation analysis. We consider three attack strategies: targeted attacks that delete structurally integral vertices, weak link attacks that delete large numbers of weakly connected vertices, and signal attacks that saturate the network with noisy signals. Results reveal that, while targeted attacks are effective when conducted at a large-scale, weak link and signal attacks deter more potential drug transactions and buyers when only a small portion of the network is attacked. We also find that intentional attacks affect network behavior. When networks are attacked, actors grow more cautious about forging ties, connecting less frequently and only to trustworthy alters. Operating in tandem, these two processes undermine long-term network robustness and increase network vulnerability to future attacks.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Computer Simulation
  • Criminals / psychology*
  • Criminals / statistics & numerical data*
  • Drug Trafficking / prevention & control*
  • Humans
  • Illicit Drugs / supply & distribution*
  • Intention
  • Models, Theoretical*
  • Social Networking*
  • Violence / psychology
  • Violence / statistics & numerical data*

Substances

  • Illicit Drugs

Grants and funding

The study is funded by the National Science Foundation, Grants: GRT00046370 and 1949037. PI: DLH. NSF website: https://www.nsf.gov/funding/pgm_summ.jsp?pims_id=5369. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.