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Research dossier · General Reference

Data loss prevention software

concept of data breach protection

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General referenceInterpretive dossier study · Crown Archives visual atlas
Record originEnglish Wikipedia
Text licenseCC BY-SA 4.0
Source revisionJul 13, 2026
Entity authorityQ373110 ↗
Source-derived summary

Data loss prevention (DLP) is a set of strategies and technologies that prevent the unauthorized transmission or disclosure of sensitive data in an information system, including data in motion (across networks), at rest (in storage), or in use (on endpoints). This concept is part of information privacy, data security and data governance. DLP systems have traditionally relied upon a variety of classification and enforcement mechanisms to reduce the risk of data loss but increasingly incorporate machine learning and behavioral analytics to enhance detection accuracy. DLP is used in on-premises systems, cloud applications, and hybrid environments.

Data loss incidents (unauthorized disclosure or deletion of sensitive data) may turn into data leak incidents (data breaches) when media containing sensitive information are lost and then acquired by an unauthorized party, including via data theft. However, a data leak is possible without losing the data on the originating side. There are limitations to the effectiveness of DLP systems in reducing risk of data loss.

Other terms associated with data leakage prevention include information leak detection and prevention (ILDP), information leak prevention (ILP), content monitoring and filtering (CMF), information protection and control (IPC), and extrusion prevention system (EPS), as opposed to an intrusion prevention system.

Categories

Technological means for prevention data loss include standard security measures, advanced/intelligent security measures, access control and encryption, and content-aware DLP systems, although only the latter category is typically referred to as DLP. Most DLP systems rely on predefined rules to identify and categorize sensitive information.

Standard measures

Standard security measures, such as firewalls, intrusion detection systems (IDSs), and antivirus software, are widely used to guard against both outsider and insider attacks.

Editorial summary

This brief starts where responsible research should: with the source description of “Data loss prevention software” as concept of data breach protection. Everything that follows is an evidence route, not borrowed authority.

Editorial reviewA practical starting point whose main value is the path it opens into stronger specialist and primary sources. The current 272-word lead offers orientation but no explicit four-digit date, so chronology should not be assumed. The selected authority fields contribute no independent date. The account is most persuasive where Data, loss and prevention can be independently traced.
Editorial analysis

Why this record matters

The subject matters to the general reference register because the source frames it as concept of data breach protection. Its deeper value depends on whether names, dates, institutions and citations support that framing.

Evidence profile

Vocabulary and entity names are the principal evidence signals here, because they determine the precision of every later search. The source revision retrieved here is dated Jul 13, 2026. The linked authority identifier is Q373110. None of the 0 selected statements returned an explicit reference.

Critical limits

The absence of detail may reflect summary conventions rather than a lack of surviving documentation. The source lead contains qualifying language; that uncertainty should survive quotation, summary and reuse. Authority statements aid reconciliation but still require their own references, qualifiers and ranks to be checked.

How to read it

Use the entry as an orientation point, then follow its citations and revision history. Names, dates and institutional relationships should be checked against the original record.

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Three-step research path

  1. Establish the record: confirm the title “Data loss prevention software”, its source revision and the description used here.
  2. Expand the search: follow Data loss prevention software primary sources, Data loss prevention software archive and Data research across catalogues and specialist indexes.
  3. Test the account: compare the strongest cited source with the responsible institution’s current record and note any disagreement.

Questions for further research

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Source & attribution

This entry incorporates text from “Data loss prevention software” on English Wikipedia. Contributors are listed in the page history. Text is available under the Creative Commons Attribution-ShareAlike 4.0 License. Selected authority identifiers and statements are retrieved from Wikidata under CC0; their references and qualifiers remain part of the verification path.