Six Years Later

Décary‐Hétu, David; Mousseau, Vincent; Vidal, Sabrina

doi:10.1177/0091450918797355

Cited by 8 publications

(2 citation statements)

References 32 publications

(52 reference statements)

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“…While 13 papers reported data collected from individual markets, one paper reported cumulative data collected from a total of 8 markets (Décary-Hétu et al, 2018). Silk Road and Silk Road 2.0 were overrepresented across the literature, being reported in 6/14 (42.9%) datasets (Bhaskar et al, 2019; Broséus et al, 2017; Dasgupta et al, 2013; Dolliver, 2015; Phelps and Watt, 2014).…”

Section: Resultsmentioning

confidence: 99%

Decrypting the cryptomarkets: Trends over a decade of the Dark Web drug trade

Sudan,

Tai,

Kim

et al. 2023

Drug Science, Policy and Law

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Introduction The Dark Web is a subsection of the Internet only accessible through specific search engines, making it impossible to trace users. Due to extensive anonymity, the drug trade on the Dark Web makes regulation complicated. We sought to uncover the scope of the online drug trade on the Dark Web and the impact it may have on the dynamics of global drug trafficking. Methods We conducted a literature review to elucidate the availability and distribution of drugs on the Dark Web based on data reported in existing literature ( n = 14) between September 2012 and June 2019. We simultaneously collected data about substances and listings from Dark Web cryptomarkets ( n = 13) active between August 2022 and January 2023. Data from the literature review and the Dark Web scrape were combined to draw trends in the chronological availability and distribution of drugs between 2012 and 2023. Results The data collected from 13 cryptomarkets between late 2022 and early 2023 showed a relative change in substance distribution compared to 2012–2019, with a decrease in prescription drugs (from >20% to <5%) and a doubling of opioid listings (from 5.5% to 9.25%), while no major changes were observed on average during 2012–2019 according to literature. Conclusions The Dark Web warrants more attention in the analysis of the global drug trade. Understanding Dark Web drug markets can inform targeted interventions and strategies to reduce drug-related harms, while ongoing research is necessary to anticipate and respond to future changes in the landscape of the illicit drug trade.

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Section: Resultsmentioning

confidence: 99%

Decrypting the cryptomarkets: Trends over a decade of the Dark Web drug trade

Sudan,

Tai,

Kim

et al. 2023

Drug Science, Policy and Law

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“…Secondly, according to the latest studies, the interest in drug sales increases on the Dark Web. In particular, researchers (Bhaskar et al, 2017), (Décary-Hétu et al, 2018), (Celestini et al, 2016) and (Minnaar, 2017) investigated marketplaces like Silkroad for their illicit drugs content. We created drug sub-classes from the detailed descriptions of the Agora labels.…”

Section: Dataset Creationmentioning

confidence: 99%

Illicit Darkweb Classification via Natural-language Processing: Classifying Illicit Content of Webpages based on Textual Information

Cascavilla,

Catolino,

Sangiovanni

2022

Proceedings of the 19th International Conference on Security and Cryptography

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This work aims at expanding previous works done in the context of illegal activities classification, performing three different steps. First, we created a heterogeneous dataset of 113995 onion sites and dark marketplaces. Then, we compared pre-trained transferable models, i.e., ULMFit (Universal Language Model Fine-tuning), Bert (Bidirectional Encoder Representations from Transformers), and RoBERTa (Robustly optimized BERT approach) with a traditional text classification approach like LSTM (Long short-term memory) neural networks. Finally, we developed two illegal activities classification approaches, one for illicit content on the Dark Web and one for identifying the specific types of drugs. Results show that Bert obtained the best approach, classifying the dark web's general content and the types of Drugs with 96.08% and 91.98% of accuracy.

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Beyond the dark web: navigating the risks of cannabis supply over the surface web

Childs

Bull

Coomber

2021

Drugs: Education, Prevention and Policy

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Common depictions of buying and selling illicit drugs online centre on how drug market actors engage in dark web drug cryptomarkets, but the supply of illicit drugs also takes place in 'plain site' on the surface web. Drawing on netnographic observations and qualitative interviews with hard-to-reach buyers and vendors (n = 20), this paper explores LeafedOut, a specific, popular surface web platform, that provides a conduit for local cannabis exchanges.We found that the platform enabled easy access and supply at the local level but increased some specific risks to those involved. Actors neutralised the perceived risks of drug supply over this surface web platform through the broader societal normalisation of cannabis use/supply, adopting encrypted messaging applications to cover 'digital traces', and developing various methods to establish trust with an exchange partner (e.g. review systems, sending selfies with drug paraphernalia, selectively choosing meet-up locations). This paper expands our understanding of the growing number of online illicit drug markets by shifting attention from dark web cryptomarkets to the much more widely accessed surface/clear web.Theoretical implications for the study of trust and risk in online illicit drug market exchanges are also considered.

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Six Years Later

Cited by 8 publications

References 32 publications

Decrypting the cryptomarkets: Trends over a decade of the Dark Web drug trade

Decrypting the cryptomarkets: Trends over a decade of the Dark Web drug trade

Illicit Darkweb Classification via Natural-language Processing: Classifying Illicit Content of Webpages based on Textual Information

Beyond the dark web: navigating the risks of cannabis supply over the surface web

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