Technology

A Data-Driven Look At Dark Web Marketplaces

Published

4 years ago

September 29, 2018

Nick Routley

View a high resolution version of this graphic.

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.

Related Topics:internet dark web ecommerce

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Technology

Infographic: Generative AI Explained by AI

What exactly is generative AI and how does it work? This infographic, created using generative AI tools such as Midjourney and ChatGPT, explains it all.

Published

2 days ago

February 1, 2023

Nick Routley

Generative AI Explained by AI

After years of research, it appears that artificial intelligence (AI) is reaching a sort of tipping point, capturing the imaginations of everyone from students saving time on their essay writing to leaders at the world’s largest tech companies. Excitement is building around the possibilities that AI tools unlock, but what exactly these tools are capable of and how they work is still not widely understood.

We could write about this in detail, but given how advanced tools like ChatGPT have become, it only seems right to see what generative AI has to say about itself.

Everything in the infographic above – from illustrations and icons to the text descriptions⁠—was created using generative AI tools such as Midjourney. Everything that follows in this article was generated using ChatGPT based on specific prompts.

Without further ado, generative AI as explained by generative AI.

Generative AI: An Introduction

Generative AI refers to a category of artificial intelligence (AI) algorithms that generate new outputs based on the data they have been trained on. Unlike traditional AI systems that are designed to recognize patterns and make predictions, generative AI creates new content in the form of images, text, audio, and more.

Generative AI uses a type of deep learning called generative adversarial networks (GANs) to create new content. A GAN consists of two neural networks: a generator that creates new data and a discriminator that evaluates the data. The generator and discriminator work together, with the generator improving its outputs based on the feedback it receives from the discriminator until it generates content that is indistinguishable from real data.

Generative AI has a wide range of applications, including:

Images: Generative AI can create new images based on existing ones, such as creating a new portrait based on a person’s face or a new landscape based on existing scenery
Text: Generative AI can be used to write news articles, poetry, and even scripts. It can also be used to translate text from one language to another
Audio: Generative AI can generate new music tracks, sound effects, and even voice acting

Disrupting Industries

People have concerns that generative AI and automation will lead to job displacement and unemployment, as machines become capable of performing tasks that were previously done by humans. They worry that the increasing use of AI will lead to a shrinking job market, particularly in industries such as manufacturing, customer service, and data entry.

Generative AI has the potential to disrupt several industries, including:

Advertising: Generative AI can create new advertisements based on existing ones, making it easier for companies to reach new audiences
Art and Design: Generative AI can help artists and designers create new works by generating new ideas and concepts
Entertainment: Generative AI can create new video games, movies, and TV shows, making it easier for content creators to reach new audiences

Overall, while there are valid concerns about the impact of AI on the job market, there are also many potential benefits that could positively impact workers and the economy.

In the short term, generative AI tools can have positive impacts on the job market as well. For example, AI can automate repetitive and time-consuming tasks, and help humans make faster and more informed decisions by processing and analyzing large amounts of data. AI tools can free up time for humans to focus on more creative and value-adding work.

How This Article Was Created

This article was created using a language model AI trained by OpenAI. The AI was trained on a large dataset of text and was able to generate a new article based on the prompt given. In simple terms, the AI was fed information about what to write about and then generated the article based on that information.

In conclusion, generative AI is a powerful tool that has the potential to revolutionize several industries. With its ability to create new content based on existing data, generative AI has the potential to change the way we create and consume content in the future.