An Analysis of Opioid Trafficking on the Surface Web

Turns out, your everyday search engine might be hiding more than comedic videos and cooking blogs. While opioid trafficking is often associated with the dark web, recent studies suggest that illegal drug markets are creeping into the more visible corners of the internet. This research set out to investigate whether opioid trafficking can be identified on the surface web by combining a custom-built web crawler with a Large Language Model (LLM) to analyze web page text. On an initial test crawl of 75 webpages, the system flagged 17 as high-confidence cases of trafficking, most involving semi-synthetic opioids like Hydrocodone and Oxycodone. Strikingly, every flagged instance was attributed to sellers, not buyers, highlighting the commercial nature of these listings. These findings suggest that the surface web is not only being used for illicit activity, but that automated tools can meaningfully detect and categorize this behavior.

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Publication Details

Journal
ScholarSpace (University of Hawaii at Manoa)
Published
2025-12-23
Primary Topic
Cybercrime and Law Enforcement Studies
Type
article
Field-Weighted Citation Impact
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article

An Analysis of Opioid Trafficking on the Surface Web

K. Ross Powell, William Bradley Glisson, Austin Adams
ScholarSpace (University of Hawaii at Manoa)
Cybercrime and Law Enforcement Studies
article

An Analysis of Opioid Trafficking on the Surface Web

K. Ross Powell, William Bradley Glisson, Austin Adams
article en

Abstract

Turns out, your everyday search engine might be hiding more than comedic videos and cooking blogs. While opioid trafficking is often associated with the dark web, recent studies suggest that illegal drug markets are creeping into the more visible corners of the internet. This research set out to investigate whether opioid trafficking can be identified on the surface web by combining a custom-built web crawler with a Large Language Model (LLM) to analyze web page text. On an initial test crawl of 75 webpages, the system flagged 17 as high-confidence cases of trafficking, most involving semi-synthetic opioids like Hydrocodone and Oxycodone. Strikingly, every flagged instance was attributed to sellers, not buyers, highlighting the commercial nature of these listings. These findings suggest that the surface web is not only being used for illicit activity, but that automated tools can meaningfully detect and categorize this behavior.

ScholarSpace (University of Hawaii at Manoa)
Gender equality
Openalex Percentile: Top 23%
Cybercrime and Law Enforcement Studies
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