The Deep Web is a concept that few people understand. Even fewer people recognize the role that big data plays in shaping it.
However, one thing is certain: advances in big data technology have played a huge role in driving changes in the deep web. It is a good idea for database developers, programmers, online businesses and other Internet technology professionals to learn about the impact that new developments in big data have had on both the surface web and deep web. Keep reading to learn more.
How Does Big Data Affect the Deep Web and Surface Web?
Surface, deep and dark webs are all names given to places on the internet that either do or don’t come up in standard search engines like Google, Yahoo, or Bing. They all rely on big data in various ways.
Sometimes they’re confused for each other, and quite often, people use at least two of them without realizing it. Here’s a breakdown of the three, followed by the reasons they’re separated and ways to use the deep web and the impact that big data has had on all of them.
Impact of Big Data on The Surface Web
When people search online for answers, advice, or something to buy, they use a search engine. These applications crawl the internet looking for helpful sites. Search engines rely on big data to archive online content for users searching for it. As Dummies points out in this article:
“Big data has made possible the development of highly capable online search engines.”
They get their results from public domain websites known as the surface web.
It’s suggested that the surface web is only 1% of what’s online, and the deep and dark webs make up the rest.
The term deep web refers to the part of the internet that doesn’t appear in surface web search engine results. It’s home to paywalled sites, private databases, and the dark web.
Many people access the deep web daily without even realizing it. Any sites that can only be accessed by subscription or a paywall don’t usually appear in surface web searches and are therefore considered deep web.
There’s potentially more information available via the deep web. People go there when they don’t have success on the surface web.
For example, a deep web background check may provide more information on a person than a surface internet search will.
Data stored on the deep web has an additional layer of privacy than information found on the surface web.
Impact of Big Data on The Dark Web
Often mistaken for each other, the deep and dark webs aren’t the same. We wrote this article to help people learn more about what the dark web is and isn’t. The Deep Web merely refers to information that is not easily accessed by the public through search engines. It can include portals on your insurance company’s website or your private Facebook messages.
While the contents of the deep web are legitimate and noncriminal, the same can’t be said for the dark web. The dark web is a marketplace of illegal activity. Drugs, trafficking, weapons, smuggling rings, and the black market for stolen credit cards can all be found here. Hackers, cyber-bots, and other nefarious activities are also housed here.
Big data technology is helping improve the state of the Deep Web. A growing number of companies are using tools like WEIDJ to extract data. Science Direct covered this in their article Web Data Extraction Approach for Deep Web using WEIDJ. This helps companies leverage the benefits of data science to provide better service to their customers using the deep web.
Big data is also helping improve the state of the Dark Web as well. Datanami states that big data has helped make the dark web brighter by fighting online crime.
Why is Data on The Surface and Deep Web Separated?
The surface web and the deep web are separate for two productive reasons: for the amount of irrelevant content and for privacy.
Most surface web searches provide results from relevant sites. The deep web contains loads of private, non-indexed, and irrelevant information that are not useful for others. If all of this data were made available, search engines would take a lot longer and provide less accurate results. Even advances in big data would not allow them to crawl all of this information.
Naturally, the reason for the dark web to be separated is that it is illegal, and only like-minded individuals will ever want to access those sites. As such, the dark web is intentionally hidden and only accessible by specific tools.
The reason for log-ins and paywalls is to protect information or make it only available to the correct people.
Search engine results won’t look for nor display this information. This makes things like a person’s Netflix viewing habits or stock-market investments private only to them.
The deep web contains a lot of secure personal information that nobody wants to be made public. It’s these pages that hackers like to hunt for.
As mentioned, many people access the deep web daily. Anyone who logs into a Gmail account or signs into a news site like the Wall Street Journal or Medium is accessing pages only found on the deep web.
The difference is that a person already needs to know the URL of the site they want to access.
Some surface websites connect with the deep web and may pay a subscription fee to access more data. This activity is beneficial when trying to get additional information on a person that’s not freely available on the surface web.
While the surface web is what most people use every day, many also access the deep web. It’s secure, personal information, only accessed via logging in, that doesn’t appear in search engine results.
Don’t confuse the deep web for the dark web. The deep web is freely available to anyone with log-in details; it’s noncriminal and legitimate. The dark web needs to be accessed by purpose-made tools and is criminal in nature.
Big Data is Key to the Evolution of the Deep Web and Surface Web
Both the Deep Web and surface web rely heavily on advances in big data technology. A growing number of online businesses are finding innovative ways to leverage big data to their benefit. They will find new ways to mine data and make it available to help customers using deep web and surface web content.