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A Data-Driven Look At Dark Web Marketplaces

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dark web markets

A Data-Driven Look At Dark Web Marketplaces

View the high resolution version of today’s graphic by clicking here.

In 2018, ex-Google CEO, Eric Schmidt, made headlines after predicting the internet would eventually split into two halves – one dominated by China and the other by the United States.

While that vision of the future may come to pass, the internet already has a noteworthy division (coincidentally related to Google): indexed and non-indexed. The indexed internet is what we’re all familiar with, everything from gif-laden Geocities websites to the webpage you’re reading this on.

Parts of the non-indexed portion of the internet may be familiar as well. This includes services like online banking, or content behind paywalls or sign-in forms. Most of this part of the internet – referred to as the Deep Web – is non-indexed.

surface deep dark web diagram

Dipping Below the Surface

Beyond easily accessible areas of the internet, lies the Dark Web, which is primarily accessed using specific software such as Tor or I2P. Practically speaking, connection requests via TOR are re-routed several times before reaching their destination. This allows people to maintain their anonymity while accessing dark web content.

The Dark Web lives in the public consciousness as a digital Wild West; a place where every vice can be explored and procured within the vacuum of lawlessness. There’s truth to the reputation, as dark net markets sell everything from illegal drugs to databases of stolen personal information. Today’s graphic, via Europe’s drug monitoring organization, EMCDDA, gives a detailed overview of dark web marketplaces going all the back to 2010.

One of the first and most well known of these markets was The Silk Road, which opened at the beginning of 2011. Around the time of its first anniversary, the market reached an estimated $22 million in annual sales.

The Short Shelf Life of Markets

Not surprisingly, governments are not thrilled at the idea of unregulated (and untaxed) markets operating in the dark web. Law enforcement and three-letter agencies have thrown considerable efforts into shutting them down, though with mixed results.

A raid on The Silk Road in 2013 did end the reign of the popular marketplace, but it had the effect of spawning dozens of new markets to help fill the void. That said, only a few end up lasting more than a year and the average lifespan of a dark web market is just eight months.

Some markets close down, or were simply a scam to begin with, but larger markets tend to fall victim to raids by law enforcement. High profile examples include Operation Onymous (2014), and Operations Bayonet and GraveSec (2017), which shut down the popular markets AlphaBay and Hansa. To give an idea of scale, Hansa reportedly offered more than 24,000 drug product listings at its height.

According to EMCDDA’s report, there are currently nine active markets. If history is any guide though, many of them will be gone by year’s end.

While giants like Google and Amazon may rule the indexed web, the commercial landscape below the surface is shifting constantly.

Update: This article has been revised to better reflect the source of the data.

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Charted: The Jobs Most Impacted by AI

We visualized the results of an analysis by the World Economic Forum, which uncovered the jobs most impacted by AI.

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Charted: The Jobs Most Impacted by AI

This was originally posted on our Voronoi app. Download the app for free on iOS or Android and discover incredible data-driven charts from a variety of trusted sources.

Large language models (LLMs) and other generative AI tools haven’t been around for very long, but they’re expected to have far-reaching impacts on the way people do their jobs. With this in mind, researchers have already begun studying the potential impacts of this transformative technology.

In this graphic, we’ve visualized the results of a World Economic Forum report, which estimated how different job departments will be exposed to AI disruption.

Data and Methodology

To identify the job departments most impacted by AI, researchers assessed over 19,000 occupational tasks (e.g. reading documents) to determine if they relied on language. If a task was deemed language-based, it was then determined how much human involvement was needed to complete that task.

With this analysis, researchers were then able to estimate how AI would impact different occupational groups.

DepartmentLarge impact (%)Small impact (%)No impact (%)
IT73261
Finance70219
Customer Sales671617
Operations651817
HR57412
Marketing56413
Legal46504
Supply Chain431839

In our graphic, large impact refers to tasks that will be fully automated or significantly altered by AI technologies. Small impact refers to tasks that have a lesser potential for disruption.

Where AI will make the biggest impact

Jobs in information technology (IT) and finance have the highest share of tasks expected to be largely impacted by AI.

Within IT, tasks that are expected to be automated include software quality assurance and customer support. On the finance side, researchers believe that AI could be significantly useful for bookkeeping, accounting, and auditing.

Still interested in AI? Check out this graphic which ranked the most commonly used AI tools in 2023.

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