n the year 2000, Michale Bergman said how searching on the internet can be compared to dragging a net across the surface of the ocean: a great deal may be caught in the net, but there is a wealth of information that is deep and therefore missed. Most of the web’s information is buried far down on sites, and standard search engines do not find it. Traditional search engines cannot see or retrieve content in the deep web. The portion of the web that is indexed by standard search engines is known as the surface web. As of 2001,[needs update] the deep web was several orders of magnitude larger than the surface web. An analogy of an iceberg has been used to represent the division between surface web and deep web respectively.
It is impossible to measure, and hard to put estimates on, the size of the deep web because the majority of the information is hidden or locked inside databases. Early estimates suggested that the deep web is 400 to 550 times larger than the surface web. However, since more information and sites are always being added, it can be assumed that the deep web is growing exponentially at a rate that cannot be quantified.
Estimates based on extrapolations from a study done at University of California, Berkeley in 2001 speculate that the deep web consists of about 7.5 petabytes. More accurate estimates are available for the number of resources in the deep web: research of He et al. detected around 300,000 deep web sites in the entire web in 2004, and, according to Shestakov, around 14,000 deep web sites existed in the Russian part of the Web in 2006.
Bergman, in a seminal paper on the deep Web published in The Journal of Electronic Publishing, mentioned that Jill Ellsworth used the term invisible Web in 1994 to refer to websites that were not registered with any search engine. Bergman cited a January 1996 article by Frank Garcia:
It would be a site that's possibly reasonably designed, but they didn't bother to register it with any of the search engines. So, no one can find them! You're hidden. I call that the invisible Web.
Another early use of the term Invisible Web was by Bruce Mount and Matthew B. Koll of Personal Library Software, in a description of the @1 deep Web tool found in a December 1996 press release.
The first use of the specific term Deep Web, now generally accepted, occurred in the aforementioned 2001 Bergman study. Content types
Methods which prevent web pages from being indexed by traditional search engines may be categorized as one or more of the following:
While it is not always possible to directly discover a specific web server’s content so that it may be indexed, a site potentially can be accessed indirectly (due to computer vulnerabilities).
To discover content on the web, search engines use web crawlers that follow hyperlinks through known protocol virtual port numbers. This technique is ideal for discovering content on the surface web but is often ineffective at finding deep web content. For example, these crawlers do not attempt to find dynamic pages that are the result of database queries due to the indeterminate number of queries that are possible. It has been noted that this can be (partially) overcome by providing links to query results, but this could unintentionally inflate the popularity for a member of the deep web.
DeepPeep, Intute, Deep Web Technologies, Scirus, and Ahmia.fi are a few search engines that have accessed the deep web. Intute ran out of funding and is now a temporary static archive as of July, 2011. Scirus retired near the end of January, 2013.
Researchers have been exploring how the deep web can be crawled in an automatic fashion, including content that can be accessed only by special software such as Tor. In 2001, Sriram Raghavan and Hector Garcia-Molina (Stanford Computer Science Department, Stanford University) presented an architectural model for a hidden-Web crawler that used key terms provided by users or collected from the query interfaces to query a Web form and crawl the Deep Web content. Alexandros Ntoulas, Petros Zerfos, and Junghoo Cho of UCLA created a hidden-Web crawler that automatically generated meaningful queries to issue against search forms). Several form query languages (e.g., DEQUEL) have been proposed that, besides issuing a query, also allow extraction of structured data from result pages. Another effort is DeepPeep, a project of the University of Utah sponsored by the National Science Foundation, which gathered hidden-web sources (web forms) in different domains based on novel focused crawler techniques.
Commercial search engines have begun exploring alternative methods to crawl the deep web. The Sitemap Protocol (first developed, and introduced by Google in 2005) and mod oai are mechanisms that allow search engines and other interested parties to discover deep web resources on particular web servers. Both mechanisms allow web servers to advertise the URLs that are accessible on them, thereby allowing automatic discovery of resources that are not directly linked to the surface web. Google’s deep web surfacing system computes submissions for each HTML form and adds the resulting HTML pages into the Google search engine index. The surfaced results account for a thousand queries per second to deep web content. In this system, the pre-computation of submissions is done using three algorithms:
selecting input values for text search inputs that accept keywords, identifying inputs which accept only values of a specific type (e.g., date), and selecting a small number of input combinations that generate URLs suitable for inclusion into the Web search index.
In 2008, to facilitate users of Tor hidden services in their access and search of a hidden .onion suffix, Aaron Swartz designed Tor2web—a proxy application able to provide access by means of common web browsers. Using this application, deep web links appear as a random string of letters followed by the .onion TLD. For example, http://xmh57jrzrnw6insl.onion links to TORCH, the Tor search engine web page. See also Portal icon Internet portal
Darknet (networking) Gopher protocol Tor2web