Emergence and structure of decentralised trade networks around dark web marketplaces

• URL: http://arxiv.org/abs/2111.01774v1
• Date: Tue, 2 Nov 2021 17:51:53 GMT
• Title: Emergence and structure of decentralised trade networks around dark web marketplaces
• Authors: Matthieu Nadini, Alberto Bracci, Abeer ElBahrawy, Philip Gradwell, Alexander Teytelboym, Andrea Baronchelli
• Abstract summary: We quantify the scale of, and thoroughly investigate, U2U trading around dark web marketplaces (DWMs) We find that half of the DWM users trade through U2U pairs generating a total trading volume greater than DWMs themselves. New U2U pairs often form while both users are active on the same DWM, suggesting the marketplace may serve as a catalyst for new direct trading relationships.
• Score: 55.41644538483948
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Dark web marketplaces (DWMs) are online platforms that facilitate illicit trade among millions of users generating billions of dollars in annual revenue. Recently, two interview-based studies have suggested that DWMs may also promote the emergence of direct user-to-user (U2U) trading relationships. Here, we quantify the scale of, and thoroughly investigate, U2U trading around DWMs by analysing 31 million Bitcoin transactions among users of 40 DWMs between June 2011 and Jan 2021. We find that half of the DWM users trade through U2U pairs generating a total trading volume greater than DWMs themselves. We then show that hundreds of thousands of DWM users form stable trading pairs that are persistent over time. Users in stable pairs are typically the ones with the largest trading volume on DWMs. Then, we show that new U2U pairs often form while both users are active on the same DWM, suggesting the marketplace may serve as a catalyst for new direct trading relationships. Finally, we reveal that stable U2U pairs tend to survive DWM closures and that they were not affected by COVID-19, indicating that their trading activity is resilient to external shocks. Our work unveils sophisticated patterns of trade emerging in the dark web and highlights the importance of investigating user behaviour beyond the immediate buyer-seller network on a single marketplace.

Related papers

• Trading Volume Maximization with Online Learning [3.8059763597999012]
  We investigate how the broker should behave to maximize the trading volume. We model the traders' valuations as an i.i.d. process with an unknown distribution. If only their willingness to sell or buy at the proposed price is revealed after each interaction, we provide an algorithm achieving poly-logarithmic regret.
  arXiv  Detail & Related papers  (2024-05-21T17:26:44Z)
• Don't Let MEV Slip: The Costs of Swapping on the Uniswap Protocol [0.17999333451993949]
  We present the first empirical characterization of the costs of trading on a decentralized exchange (DEX) Using quoted prices from the Uniswap Labs interface, we evaluate the efficiency of trading on DEXs. Our results provide preliminary evidence that DEXs offer a compelling trust-less alternative to centralized exchanges for trading digital assets.
  arXiv  Detail & Related papers  (2023-09-24T14:22:15Z)
• Identifying key players in dark web marketplaces [58.720142291102135]
  This paper aims to identify the key players in Bitcoin transaction networks linked to dark markets. We show that a large fraction of the traded volume is concentrated in a small group of elite market participants. Our findings suggest that understanding the behavior of key players in dark web marketplaces is critical to effectively disrupting illegal activities.
  arXiv  Detail & Related papers  (2023-06-15T20:30:43Z)
• A Game of NFTs: Characterizing NFT Wash Trading in the Ethereum Blockchain [59.0626764544669]
  The Non-Fungible Token (NFT) market experienced explosive growth in 2021, with a monthly trade volume reaching $6 billion in January 2022. Concerns have emerged about possible wash trading, a form of market manipulation in which one party repeatedly trades an NFT to inflate its volume artificially. We find that wash trading affects 5.66% of all NFT collections, with a total artificial volume of $3,406,110,774.
  arXiv  Detail & Related papers  (2022-12-02T15:03:35Z)
• The Recurrent Reinforcement Learning Crypto Agent [0.0]
  We demonstrate an application of online transfer learning as a digital assets trading agent. The agent learns to trade the XBTUSD (Bitcoin versus US dollars) perpetual swap derivatives contract on BitMEX. Overall, our crypto agent realises a total return of 350%, net of transaction costs, over roughly five years.
  arXiv  Detail & Related papers  (2022-01-12T21:00:43Z)
• Macroscopic properties of buyer-seller networks in online marketplaces [55.41644538483948]
  We analyze two datasets containing 245M transactions that took place on online marketplaces between 2010 and 2021. We show that transactions in online marketplaces exhibit strikingly similar patterns despite significant differences in language, lifetimes, products, regulation, and technology.
  arXiv  Detail & Related papers  (2021-12-16T18:00:47Z)
• The illicit trade of COVID-19 vaccines on the dark web [55.45786602961871]
  Early analyses revealed that dark web marketplaces (DWMs) started offering COVID-19 related products (e.g., masks and COVID-19 tests) as soon as the COVID-19 pandemic started. Here, we broaden the scope and depth of previous investigations by analysing 194 DWMs until July 2021, including the crucial period in which vaccines became available. We show that recreational drugs are the most affected among traditional DWMs product, with COVID-19 mentions steadily increasing since March 2020.
  arXiv  Detail & Related papers  (2021-02-10T14:52:54Z)
• Dark Web Marketplaces and COVID-19: before the vaccine [53.447910186085586]
  We analyse 851,199 listings extracted from 30 dark web marketplaces between January 1, 2020 and November 16, 2020. We identify 788 listings directly related to COVID-19 products and monitor the temporal evolution of product categories. We reveal how the online shadow economy has evolved during the COVID-19 pandemic and highlight the importance of a continuous monitoring of DWMs.
  arXiv  Detail & Related papers  (2020-08-04T14:27:41Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.