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Deep web (search)

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Deep web (search)

The Deep Web, Deep Net,[1] Invisible Web,[2] or Hidden Web[3] are search terms referring to the content on the World Wide Web that is not indexed by standard search engines. Computer scientist Mike Bergman is credited with coining the term in 2000.[4]


  • Terminology conflation 1
  • Size 2
  • Non-indexed content 3
  • Content types 4
  • Indexing methodologies 5
  • See also 6
  • References 7
  • Further reading 8

Terminology conflation

The first conflation of the terms came about in 2009 when the deep web search terminology was discussed alongside illegal activities taking place on the Freenet darknet.[5]

Since then, the use in the Silk Road's media reporting, many[6][7][8] people and media outlets, have taken to using Deep Web synonymously with the Dark Web or Darknet, a comparison Bright Planet rejects as inaccurate[9] and consequently is an ongoing source of confusion.[10] Wired reporters Kim Zetter[11] and Andy Greenberg[12] recommend the terms be used in distinct fashions.


In the year 2000, Michael K. 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.[13] 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, the deep web was several orders of magnitude larger than the surface web.[14] 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 harsh 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[14] 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,[15] and, according to Shestakov, around 14,000 deep web sites existed in the Russian part of the Web in 2006.[16]

Non-indexed content

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.[14] Bergman cited a January 1996 article by Frank Garcia:[17]

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.[18]

The first use of the specific term Deep Web, now generally accepted, occurred in the aforementioned 2001 Bergman study.[14]

Content types

Methods which prevent web pages from being indexed by traditional search engines may be categorized as one or more of the following:

  1. Contextual Web: pages with content varying for different access contexts (e.g., ranges of client IP addresses or previous navigation sequence).
  2. Dynamic content: dynamic pages which are returned in response to a submitted query or accessed only through a form, especially if open-domain input elements (such as text fields) are used; such fields are hard to navigate without domain knowledge.
  3. Limited access content: sites that limit access to their pages in a technical way (e.g., using the Robots Exclusion Standard or CAPTCHAs, or no-store directive which prohibit search engines from browsing them and creating cached copies).[19]
  4. Non-HTML/text content: textual content encoded in multimedia (image or video) files or specific file formats not handled by search engines.
  5. Private Web: sites that require registration and login (password-protected resources).
  6. Scripted content: pages that are only accessible through links produced by JavaScript as well as content dynamically downloaded from Web servers via Flash or Ajax solutions.
  7. Software: certain content is intentionally hidden from the regular Internet, accessible only with special software, such as Tor, I2P, or other darknet software. For example, Tor allows users to access websites using the .onion host suffix anonymously, hiding their IP address.
  8. Unlinked content: pages which are not linked to by other pages, which may prevent web crawling programs from accessing the content. This content is referred to as pages without backlinks (also known as inlinks). Also, search engines do not always detect all backlinks from searched web pages.
  9. Web archives: Web archival services such as the Wayback Machine enable users to see archived versions of web pages across time, including websites which have become inaccessible, and are not indexed by search engines such as Google.[20]

Indexing methodologies

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.[4] 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 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.[21] Scirus retired near the end of January 2013.[22]

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)[23][24] 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).[25] Several form query languages (e.g., DEQUEL[26]) 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.[27][28]

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.[29] In this system, the pre-computation of submissions is done using three algorithms:

  1. selecting input values for text search inputs that accept keywords,
  2. identifying inputs which accept only values of a specific type (e.g., date), and
  3. 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.[30] 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


  1. ^ Hamilton, Nigel. "The Mechanics of a Deep Net Metasearch Engine".  
  2. ^ Devine, Jane; Egger-Sider, Francine (July 2004). "Beyond google: the invisible web in the academic library". The Journal of Academic Librarianship 30 (4): 265–269.  
  3. ^ Raghavan, Sriram; Garcia-Molina, Hector (11–14 September 2001). "Crawling the Hidden Web". 27th International Conference on Very Large Data Bases (Rome, Italy). 
  4. ^ a b Wright, Alex (2009-02-22). "Exploring a 'Deep Web' That Google Can’t Grasp". The New York Times. Retrieved 2009-02-23. 
  5. ^ Beckett, Andy (26 November 2009). "The dark side of the internet". Retrieved 9 August 2015. 
  6. ^ Deep Web (film)
  7. ^ Daily Mail Reporter (11 October 2013). "The disturbing world of the Deep Web, where contract killers and drug dealers ply their trade on the internet". Retrieved 25 May 2015. 
  8. ^ "NASA is indexing the 'Deep Web' to show mankind what Google won't". Fusion. 
  9. ^ "Clearing Up Confusion – Deep Web vs. Dark Web". BrightPlanet. 
  10. ^ Solomon, Jane (6 May 2015). "The Deep Web vs. The Dark Web". Retrieved 26 May 2015. 
  11. ^ NPR Staff (25 May 2014). "Going Dark: The Internet Behind The Internet". Retrieved 29 May 2015. 
  12. ^ Greenberg, Andy (19 November 2014). "Hacker Lexicon: What Is the Dark Web?". Retrieved 6 June 2015. 
  13. ^ Bergman, Michael K (July 2000). The Deep Web: Surfacing Hidden Value (PDF). BrightPlanet LLC. 
  14. ^ a b c d Bergman, Michael K (August 2001). "The Deep Web: Surfacing Hidden Value". The Journal of Electronic Publishing 7 (1).  
  15. ^ He, Bin; Patel, Mitesh; Zhang, Zhen; Chang, Kevin Chen-Chuan (May 2007). "Accessing the Deep Web: A Survey". Communications of the ACM (CACM) 50 (2): 94–101.  
  16. ^ Shestakov, Denis (2011). "Sampling the National Deep Web" (PDF). pp. 331–340. 
  17. ^ Garcia, Frank (January 1996). "Business and Marketing on the Internet". Masthead 15 (1). Archived from the original on 1996-12-05. Retrieved 2009-02-24. 
  18. ^ @1 started with 5.7 terabytes of content, estimated to be 30 times the size of the nascent World Wide Web; PLS was acquired by AOL in 1998 and @1 was abandoned. "PLS introduces AT1, the first 'second generation' Internet search service" (Press release). Personal Library Software. December 1996. Retrieved 2009-02-24. 
  19. ^ "Hypertext Transfer Protocol (HTTP/1.1): Caching".  
  20. ^ Wiener-Bronner, Danielle (10 June 2015). "NASA is indexing the ‘Deep Web’ to show mankind what Google won’t". Fusion. Retrieved 27 June 2015. There are other simpler versions of Memex already available. “If you’ve ever used the Internet Archive‘s Wayback Machine,” which gives you past versions of a website not accessible through Google, then you’ve technically searched the Deep Web, said Mattmann. 
  21. ^ "Intute FAQ". Retrieved October 13, 2012. 
  22. ^ "Elsevier to Retire Popular Science Search Engine". December 2013. Retrieved 22 June 2015. by end of January 2014, Elsevier will be discontinuing Scirus, its free science search engine. Scirus has been a wide-ranging research tool, with over 575 million items indexed for searching, including webpages, pre-print articles, patents, and repositories. 
  23. ^ Sriram Raghavan; Garcia-Molina, Hector (2000). "Crawling the Hidden Web" (PDF). Stanford Digital Libraries Technical Report. Retrieved 2008-12-27. 
  24. ^ Raghavan, Sriram; Garcia-Molina, Hector (2001). "Crawling the Hidden Web" (PDF). Proceedings of the 27th International Conference on Very Large Data Bases (VLDB). pp. 129–38. 
  25. ^ Alexandros, Ntoulas; Zerfos, Petros; Cho, Junghoo (2005). "Downloading Hidden Web Content" (PDF).  
  26. ^ Shestakov, Denis; Bhowmick, Sourav S.; Lim, Ee-Peng (2005). "DEQUE: Querying the Deep Web" (PDF). Data & Knowledge Engineering 52(3): 273–311. 
  27. ^ Barbosa, Luciano;  
  28. ^ Barbosa, Luciano;  
  29. ^ Madhavan, Jayant; Ko, David; Kot, Łucja; Ganapathy, Vignesh; Rasmussen, Alex; Halevy, Alon (2008). "Google’s Deep-Web Crawl" (PDF). VLDB Endowment, ACM. Retrieved 2009-04-17. 
  30. ^ Aaron, Swartz. "In Defense of Anonymity". Retrieved 4 February 2014. 

Further reading

  • Barker, Joe (Jan 2004), "Invisible Web: What it is, Why it exists, How to find it, and its inherent ambiguity", Teaching Library Internet Workshops, Berkeley, CA, USA: UC .
  • Basu, Saikat (March 14, 2010), 10 Search Engines to Explore the Invisible Web, .
  • Ozkan, Akin (Nov 2014), DEEP WEB /DERİN İNTERNET .
  • Gruchawka, Steve (June 2006), How-To Guide to the Deep Web .
  • Hamilton, Nigel (2003), The Mechanics of a Deep Net Metasearch Engine, 12th World Wide Web Conference .
  • He, Bin; Chang, Kevin Chen-Chuan (2003). "Statistical Schema Matching across Web Query Interfaces" (PDF). Proceedings of the 2003 ACM SIGMOD International Conference on Management of Data. Archived from the original (PDF) on 20 July 2011. 
  • Howell O'Neill, Patrick (October 2013), How to search the Deep Web, The Daily Dot .
  • Ipeirotis, Panagiotis G.; Gravano, Luis; Sahami, Mehran (2001). "Probe, Count, and Classify: Categorizing Hidden-Web Databases" (PDF). Proceedings of the 2001 ACM SIGMOD International Conference on Management of Data. pp. 67–78. 
  • King, John D.; Li, Yuefeng; Tao, Daniel; Nayak, Richi (November 2007). "Mining World Knowledge for Analysis of Search Engine Content" (PDF). Web Intelligence and Agent Systems: an International Journal 5 (3): 233–53. 
  • McCown, Frank; Liu, Xiaoming; Nelson, Michael L.; Zubair, Mohammad (March–April 2006). "Search Engine Coverage of the OAI-PMH Corpus" (PDF).  
  • Shestakov, Denis (June 2008). Search Interfaces on the Web: Querying and Characterizing. TUCS Doctoral Dissertations 104, University of Turku
  • Whoriskey, Peter (December 11, 2008), "Firms Push for a More Searchable Federal Web", The Washington Post: D01 .
  • Wright, Alex (Mar 2004), "In Search of the Deep Web", Salon, archived from the original on 9 March 2007 .
  • Scientists, Naked (Dec 2014). "The Internet: the good, the bad and the ugly - In-depth exploration of the Internet and the Dark Web by Cambridge University's Naked Scientists" (Podcast). 
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