Deep web
The
deep web,[1]
invisible web,[2] or hidden
web[3]
are parts of the World Wide Web whose contents are not indexed by standard search
engines for any reason. The content is hidden behind HTML forms.[4] [5] The
opposite term to the deep web is the surface
web. The deep web includes many very common uses such as web mail and
online
banking but also paid for services with a paywall such as video
on demand, and many more. Computer
scientist Michael K. Bergman is credited with coining the term deep web
in 2001 as a search indexing term.[6]
Contents
- 1 Terminology
- 2 Size
- 3 Non-indexed content
- 4 Content types
- 5 Indexing methods
- 6 See also
- 7 References
- 8 Further reading
Terminology
Further information: Dark web
The
first conflation
of the terms "deep web" and "dark web"
came about in 2009 when the deep web search terminology was discussed alongside
illegal activities taking place on the Freenet darknet.[7]
Since
then, the use in the Silk Road's media reporting, many[8][9] people
and media outlets, have taken to using Deep Web synonymously
with the dark
web or darknet,
a comparison many reject as inaccurate[10]
and consequently is an ongoing source of confusion.[11] Wired
reporters Kim
Zetter[12]
and Andy Greenberg[13]
recommend the terms be used in distinct fashions. While the deep web is
reference to any site that cannot be accessed through a traditional search
engine, the dark web is a small portion of the deep web that has been
intentionally hidden and is inaccessible through standard browsers and methods.[14][15][16][17][18]
Size
In
the year 2001, 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.[19]
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.[20]
An analogy of an iceberg
used by Denis Shestakov represents 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[20]
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,[21]
and, according to Shestakov, around 14,000 deep web sites existed in the
Russian part of the Web in 2006.[22]
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.[20]
Bergman cited a January 1996 article by Frank Garcia:[23]
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.[24]
The
first use of the specific term deep web, now generally accepted,
occurred in the aforementioned 2001 Bergman study.[20]
Content types
Methods
which prevent web pages from being indexed by traditional search engines may be
categorized as one or more of the following:
- Contextual Web: pages with content varying for different access contexts (e.g., ranges of client IP addresses or previous navigation sequence).
- 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.
- 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).[25]
- Non-HTML/text content: textual content encoded in multimedia (image or video) files or specific file formats not handled by search engines.
- Private Web: sites that require registration and login (password-protected resources).
- 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.
- 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 server address anonymously, hiding their IP address.
- 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.
- 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.[26]
Indexing methods
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.[6]
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.[27]
Scirus retired near the end of January 2013.[28]
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)[29][30]
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.[31]
Several form query languages (e.g., DEQUEL[32]) 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.[33][34]
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.[35] 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.[36]
Using this application, deep web links appear as a random string of letters
followed by the .onion TLD.
References
Hamilton, Nigel. "The Mechanics of a Deep Net Metasearch
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Devine, Jane; Egger-Sider,
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Raghavan, Sriram;
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Madhavan, J., Ko, D., Kot, Ł.,
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Shedden, Sam (June 8, 2014).
"How
Do You Want Me to Do It? Does It Have to Look like an Accident? – an Assassin
Selling a Hit on the Net; REVEALED INSIDE THE DEEP WEB". Sunday Mail. Trinity
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Wright, Alex (2009-02-22). "Exploring
a 'Deep Web' That Google Can’t Grasp". The New York Times. Retrieved 2009-02-23.
Beckett, Andy (26 November
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disturbing world of the Deep Web, where contract killers and drug dealers ply
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"Clearing
Up Confusion – Deep Web vs. Dark Web". BrightPlanet.
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January 2017.
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is the dark web and who uses it?". The Globe and Mail. Retrieved 15
January 2017.
Bergman, Michael K (August
2001). "The
Deep Web: Surfacing Hidden Value". The Journal of Electronic
Publishing. 7 (1). doi:10.3998/3336451.0007.104.
He, Bin; Patel, Mitesh;
Zhang, Zhen; Chang, Kevin Chen-Chuan (May 2007). "Accessing the Deep Web:
A Survey". Communications of the ACM. 50 (2): 94–101. doi:10.1145/1230819.1241670.
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1996). "Business
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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 Chris
Mattmann.
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tool, with over 575 million items indexed for searching, including webpages,
pre-print articles, patents, and repositories.
Sriram Raghavan;
Garcia-Molina, Hector (2000). "Crawling the
Hidden Web" (PDF). Stanford Digital Libraries Technical Report. Retrieved 2008-12-27.
Raghavan, Sriram;
Garcia-Molina, Hector (2001). "Crawling the
Hidden Web" (PDF). Proceedings of the 27th International Conference on Very
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Alexandros, Ntoulas; Zerfos,
Petros; Cho, Junghoo (2005). "Downloading
Hidden Web Content" (PDF). UCLA Computer Science.
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Shestakov, Denis; Bhowmick,
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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, MakeUseOf.com.
- 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). IEEE Internet Computing. 10 (2): 66–73. doi:10.1109/MIC.2006.41.
- Price, Gary; Sherman, Chris (July 2001). The Invisible Web: Uncovering Information Sources Search Engines Can't See. CyberAge Books. ISBN 0-910965-51-X.
- 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, p. 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).