SherbyNet - /page/wikibook/entry.mu

Micron Document

<!DOCTYPE html>

<title>Data anonymization</title>

</head>

<span id="openzim-page-title" class="mw-page-title-main"><span class="mw-page-title-main">Data anonymization</span></span>

</h1>

</header>

/* start https://en.wikipedia.org/ */

.mw-parser-output .hatnote{font-style:italic}.mw-parser-output div.hatnote{padding-left:1.6em;margin-bottom:0.5em}.mw-parser-output .hatnote i{font-style:normal}.mw-parser-output .hatnote+link+.hatnote{margin-top:-0.5em}@media print{body.ns-0 .mw-parser-output .hatnote{display:none!important}}

/* end https://en.wikipedia.org/ */

</style><div role="note" class="hatnote navigation-not-searchable">"Anonymization" redirects here. For anonymity on the Internet, see <a href="Anonymity#Anonymity_on_the_Internet" title="Anonymity">Anonymity § Anonymity on the Internet</a>.</div>

<div role="note" class="hatnote navigation-not-searchable">Not to be confused with <a href="Data_cleansing" title="Data cleansing">Data cleansing</a>.</div>

<p><b>Data anonymization</b> is a type of <a href="Sanitization_(classified_information)" class="mw-redirect" title="Sanitization (classified information)">information sanitization</a> whose intent is <a href="Privacy_protection" class="mw-redirect" title="Privacy protection">privacy protection</a>. It is the process of removing <a href="Personally_identifiable_information" class="mw-redirect" title="Personally identifiable information">personally identifiable information</a> from <a href="Data_set" title="Data set">data sets</a>, so that the people whom the data describe remain <a href="Anonymity" title="Anonymity">anonymous</a>.

</p>

<div class="mw-heading mw-heading2"><h2 id="Overview">Overview</h2></div>

<p>Data anonymization has been defined as a "process by which personal data is altered in such a way that a data subject can no longer be identified directly or indirectly, either by the data controller alone or in collaboration with any other party."<sup id="cite_ref-1" class="reference"><a href="#cite_note-1"><span class="cite-bracket">[</span>1<span class="cite-bracket">]</span></a></sup> Data anonymization may enable the transfer of information across a boundary, such as between two departments within an agency or between two agencies, while reducing the risk of unintended disclosure, and in certain environments in a manner that enables evaluation and analytics post-anonymization.

</p><p>In the context of <a href="Medical_record" title="Medical record">medical data</a>, anonymized data refers to data from which the patient cannot be identified by the recipient of the information. The name, address, and full postcode must be removed, together with any other information which, in conjunction with other data held by or disclosed to the recipient, could identify the patient.<sup id="cite_ref-2" class="reference"><a href="#cite_note-2"><span class="cite-bracket">[</span>2<span class="cite-bracket">]</span></a></sup>

</p><p>There will always be a risk that anonymized data may not stay anonymous over time. Pairing the anonymized dataset with other data, clever techniques and raw power are some of the ways previously anonymous data sets have become de-anonymized; The data subjects are no longer anonymous.

</p><p><a href="De-anonymization" class="mw-redirect" title="De-anonymization">De-anonymization</a> is the reverse process in which anonymous data is cross-referenced with other data sources to re-identify the anonymous data source.<sup id="cite_ref-3" class="reference"><a href="#cite_note-3"><span class="cite-bracket">[</span>3<span class="cite-bracket">]</span></a></sup>

Generalization and perturbation are the two popular anonymization approaches for relational data.<sup id="cite_ref-4" class="reference"><a href="#cite_note-4"><span class="cite-bracket">[</span>4<span class="cite-bracket">]</span></a></sup> The process of obscuring data with the ability to re-identify it later is also called <a href="Pseudonymization" title="Pseudonymization">pseudonymization</a> and is one way companies can store data in a way that is <a href="Health_Insurance_Portability_and_Accountability_Act" title="Health Insurance Portability and Accountability Act">HIPAA</a> compliant.

</p><p>However, according to ARTICLE 29 DATA PROTECTION WORKING PARTY, Directive 95/46/EC refers to anonymisation in Recital 26 "signifies that to anonymise any data, the data must be stripped of sufficient elements such that the data subject can no longer be identified. More precisely, that data must be processed in such a way that it can no longer be used to identify a natural person by using “all the means likely reasonably to be used” by either the controller or a third party. An important factor is that the processing must be irreversible. The Directive does not clarify how such a de-identification process should or could be performed. The focus is on the outcome: that data should be such as not to allow the data subject to be identified via “all” “likely” and “reasonable” means. Reference is made to codes of conduct as a tool to set out possible anonymisation mechanisms as well as retention in a form in which identification of the data subject is “no longer possible”.<sup id="cite_ref-OAT_1_5-0" class="reference"><a href="#cite_note-OAT_1-5"><span class="cite-bracket">[</span>5<span class="cite-bracket">]</span></a></sup>

</p><p>There are five types of data anonymization operations: generalization, suppression, anatomization, permutation, and perturbation.<sup id="cite_ref-:0_6-0" class="reference"><a href="#cite_note-:0-6"><span class="cite-bracket">[</span>6<span class="cite-bracket">]</span></a></sup>

</p>

<div class="mw-heading mw-heading2"><h2 id="GDPR_requirements">GDPR requirements</h2></div>

<p>The <a href="European_Union" title="European Union">European Union</a>'s <a href="General_Data_Protection_Regulation" title="General Data Protection Regulation">General Data Protection Regulation</a> (GDPR) requires that stored data on people in the EU undergo either anonymization or a <a href="Pseudonymization" title="Pseudonymization">pseudonymization</a> process.<sup id="cite_ref-7" class="reference"><a href="#cite_note-7"><span class="cite-bracket">[</span>7<span class="cite-bracket">]</span></a></sup> GDPR Recital (26) establishes a very high bar for what constitutes anonymous data, thereby exempting the data from the requirements of the GDPR, namely “…information which does not relate to an identified or identifiable natural person or to personal data rendered anonymous in such a manner that the data subject is not or no longer identifiable.” The European Data Protection Supervisor (EDPS) and the Spanish Agencia Española de Protección de Datos (AEPD) have issued joint guidance related to requirements for anonymity and exemption from GDPR requirements. According to the EDPS and AEPD, no one, including the data controller, should be able to re-identify data subjects in a properly anonymized dataset.<sup id="cite_ref-ITH_1_8-0" class="reference"><a href="#cite_note-ITH_1-8"><span class="cite-bracket">[</span>8<span class="cite-bracket">]</span></a></sup> Research by data scientists at Imperial College in London and <a href="UCLouvain" title="UCLouvain">UCLouvain</a> in Belgium,<sup id="cite_ref-9" class="reference"><a href="#cite_note-9"><span class="cite-bracket">[</span>9<span class="cite-bracket">]</span></a></sup> as well as a ruling by Judge Michal Agmon-Gonen of the Tel Aviv District Court,<sup id="cite_ref-10" class="reference"><a href="#cite_note-10"><span class="cite-bracket">[</span>10<span class="cite-bracket">]</span></a></sup> highlight the shortcomings of "Anonymisation" in today's <a href="Big_data" title="Big data">big data</a> world. Anonymisation reflects an outdated approach to data protection that was developed when the processing of data was limited to isolated (siloed) applications, prior to the popularity of big data processing involving the widespread sharing and combining of data.<sup id="cite_ref-11" class="reference"><a href="#cite_note-11"><span class="cite-bracket">[</span>11<span class="cite-bracket">]</span></a></sup>

</p>

<div class="mw-heading mw-heading2"><h2 id="Anonymization_of_different_types_of_data">Anonymization of different types of data</h2></div>

<p>Structured data:

</p>

<ul><li><a href="Databases" class="mw-redirect" title="Databases">Databases</a></li></ul>

<p>Unstructured data:

</p>

<ul><li><a href="PDF_files" class="mw-redirect" title="PDF files">PDF files</a> - Anonymization of text, tables, images, scanned pages.</li>

<li><a href="DICOM" title="DICOM">DICOM</a> - Anonymization metadata, pixel data, overlay data, encapsulated documents.<sup id="cite_ref-12" class="reference"><a href="#cite_note-12"><span class="cite-bracket">[</span>12<span class="cite-bracket">]</span></a></sup></li>

<li><a href="Images" class="mw-redirect" title="Images">Images</a></li></ul>

<p>Removing identifying <a href="Metadata" title="Metadata">metadata</a> from <a href="Computer_files" class="mw-redirect" title="Computer files">computer files</a> is important for anonymizing them. <a href="Metadata_removal_tool" title="Metadata removal tool">Metadata removal tools</a> are useful for achieving this.

</p>

<ul><li><a href="Anonymity" title="Anonymity">Anonymity</a></li>

<li><a href="De-anonymization" class="mw-redirect" title="De-anonymization">De-anonymization</a></li>

<li><a href="De-identification" title="De-identification">De-identification</a></li>

<li><a href="Differential_privacy" title="Differential privacy">Differential privacy</a></li>

<li><a href="Fillet_(redaction)" title="Fillet (redaction)">Fillet (redaction)</a></li>

<li><a href="Geo-Blocking" class="mw-redirect" title="Geo-Blocking">Geo-Blocking</a></li>

<li><a href="K-anonymity" title="K-anonymity">k-anonymity</a></li>

<li><a href="L-diversity" title="L-diversity">l-diversity</a></li>

<li><a href="Masking_and_unmasking_by_intelligence_agencies" class="mw-redirect" title="Masking and unmasking by intelligence agencies">Masking and unmasking by intelligence agencies</a></li>

<li><a href="Metadata_removal_tool" title="Metadata removal tool">Metadata removal tool</a></li>

<li><a href="Pseudonymization" title="Pseudonymization">Pseudonymization</a></li>

<li><a href="Statistical_disclosure_control" title="Statistical disclosure control">Statistical disclosure control</a></li></ul>

<div class="mw-heading mw-heading2"><h2 id="References">References</h2></div>

/* start https://en.wikipedia.org/ */

.mw-parser-output .reflist{margin-bottom:0.5em;list-style-type:decimal}@media screen{.mw-parser-output .reflist{font-size:90%}}.mw-parser-output .reflist .references{font-size:100%;margin-bottom:0;list-style-type:inherit}.mw-parser-output .reflist-columns-2{column-width:30em}.mw-parser-output .reflist-columns-3{column-width:25em}.mw-parser-output .reflist-columns{margin-top:0.3em}.mw-parser-output .reflist-columns ol{margin-top:0}.mw-parser-output .reflist-columns li{page-break-inside:avoid;break-inside:avoid-column}.mw-parser-output .reflist-upper-alpha{list-style-type:upper-alpha}.mw-parser-output .reflist-upper-roman{list-style-type:upper-roman}.mw-parser-output .reflist-lower-alpha{list-style-type:lower-alpha}.mw-parser-output .reflist-lower-greek{list-style-type:lower-greek}.mw-parser-output .reflist-lower-roman{list-style-type:lower-roman}

/* end https://en.wikipedia.org/ */

</style><div class="reflist">

/* start https://en.wikipedia.org/ */

.mw-parser-output cite.citation{font-style:inherit;word-wrap:break-word}.mw-parser-output .citation q{quotes:"\"""\"""'""'"}.mw-parser-output .citation:target{background-color:rgba(0,127,255,0.133)}.mw-parser-output .id-lock-free.id-lock-free a{background:url("./mw/Lock-green.svg")right 0.1em center/9px no-repeat}.mw-parser-output .id-lock-limited.id-lock-limited a,.mw-parser-output .id-lock-registration.id-lock-registration a{background:url("./mw/Lock-gray-alt-2.svg")right 0.1em center/9px no-repeat}.mw-parser-output .id-lock-subscription.id-lock-subscription a{background:url("./mw/Lock-red-alt-2.svg")right 0.1em center/9px no-repeat}.mw-parser-output .cs1-ws-icon a{background:url("./mw/Wikisource-logo.svg")right 0.1em center/12px no-repeat}body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-free a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-limited a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-registration a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-subscription a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .cs1-ws-icon a{background-size:contain;padding:0 1em 0 0}.mw-parser-output .cs1-code{color:inherit;background:inherit;border:none;padding:inherit}.mw-parser-output .cs1-hidden-error{display:none;color:var(--color-error,#d33)}.mw-parser-output .cs1-visible-error{color:var(--color-error,#d33)}.mw-parser-output .cs1-maint{display:none;color:#085;margin-left:0.3em}.mw-parser-output .cs1-kern-left{padding-left:0.2em}.mw-parser-output .cs1-kern-right{padding-right:0.2em}.mw-parser-output .citation .mw-selflink{font-weight:inherit}@media screen{.mw-parser-output .cs1-format{font-size:95%}html.skin-theme-clientpref-night .mw-parser-output .cs1-maint{color:#18911f}}@media screen and (prefers-color-scheme:dark){html.skin-theme-clientpref-os .mw-parser-output .cs1-maint{color:#18911f}}

/* end https://en.wikipedia.org/ */

</style><cite class="citation book cs1"><a rel="nofollow" class="external text" href="https://www.iso.org/standard/63553.html"><i>ISO 25237:2017 Health informatics -- Pseudonymization</i></a>. ISO. 2017. p. 7.</cite></span>

</li>

<li id="cite_note-2"><span class="mw-cite-backlink"><b><a href="#cite_ref-2">^</a></b></span> <span class="reference-text"><cite class="citation web cs1"><a rel="nofollow" class="external text" href="http://medical-dictionary.thefreedictionary.com/Anonymized+Data">"Data anonymization"</a>. <i>The Free Medical Dictionary</i><span class="reference-accessdate">. Retrieved <span class="nowrap">17 January</span> 2014</span>.</cite></span>

</li>

<li id="cite_note-3"><span class="mw-cite-backlink"><b><a href="#cite_ref-3">^</a></b></span> <span class="reference-text"><cite class="citation web cs1"><a rel="nofollow" class="external text" href="http://whatis.techtarget.com/definition/de-anonymization-deanonymization">"De-anonymization"</a>. Whatis.com<span class="reference-accessdate">. Retrieved <span class="nowrap">17 January</span> 2014</span>.</cite></span>

</li>

<li id="cite_note-4"><span class="mw-cite-backlink"><b><a href="#cite_ref-4">^</a></b></span> <span class="reference-text"><cite id="CITEREFBin_ZhouJian_PeiWoShun_Luk2008" class="citation journal cs1">Bin Zhou; Jian Pei; WoShun Luk (December 2008). <a rel="nofollow" class="external text" href="https://www.cs.sfu.ca/~jpei/publications/SocialNetworkAnonymization_survey.pdf">"A brief survey on anonymization techniques for privacy preserving publishing of social network data"</a> <span class="cs1-format">(PDF)</span>. <i>ACM SIGKDD Explorations Newsletter</i>. <b>10</b> (2): <span class="nowrap">12–</span>22. <a href="Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1145%2F1540276.1540279">10.1145/1540276.1540279</a>. <a href="S2CID_(identifier)" class="mw-redirect" title="S2CID (identifier)">S2CID</a> <a rel="nofollow" class="external text" href="https://api.semanticscholar.org/CorpusID:609178">609178</a>.</cite></span>

</li>

<li id="cite_note-OAT_1-5"><span class="mw-cite-backlink"><b><a href="#cite_ref-OAT_1_5-0">^</a></b></span> <span class="reference-text"><cite class="citation web cs1"><a rel="nofollow" class="external text" href="https://ec.europa.eu/justice/article-29/documentation/opinion-recommendation/files/2014/wp216_en.pdf">"Opinion 05/2014 on Anonymisation Techniques"</a> <span class="cs1-format">(PDF)</span>. <a href="EU_Commission" class="mw-redirect" title="EU Commission">EU Commission</a>. 10 April 2014<span class="reference-accessdate">. Retrieved <span class="nowrap">31 December</span> 2023</span>.</cite></span>

</li>

<li id="cite_note-:0-6"><span class="mw-cite-backlink"><b><a href="#cite_ref-:0_6-0">^</a></b></span> <span class="reference-text"><cite id="CITEREFEyupogluAydinZaimSertbas2018" class="citation journal cs1">Eyupoglu, Can; Aydin, Muhammed; Zaim, Abdul; Sertbas, Ahmet (2018-05-17). <a rel="nofollow" class="external text" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7512893">"An Efficient Big Data Anonymization Algorithm Based on Chaos and Perturbation Techniques"</a>. <i>Entropy</i>. <b>20</b> (5): 373. <a href="Bibcode_(identifier)" class="mw-redirect" title="Bibcode (identifier)">Bibcode</a>:<a rel="nofollow" class="external text" href="https://ui.adsabs.harvard.edu/abs/2018Entrp..20..373E">2018Entrp..20..373E</a>. <a href="Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<span class="id-lock-free" title="Freely accessible"><a rel="nofollow" class="external text" href="https://doi.org/10.3390%2Fe20050373">10.3390/e20050373</a></span>. <a href="ISSN_(identifier)" class="mw-redirect" title="ISSN (identifier)">ISSN</a> <a rel="nofollow" class="external text" href="https://search.worldcat.org/issn/1099-4300">1099-4300</a>. <a href="PMC_(identifier)" class="mw-redirect" title="PMC (identifier)">PMC</a> <span class="id-lock-free" title="Freely accessible"><a rel="nofollow" class="external text" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7512893">7512893</a></span>. <a href="PMID_(identifier)" class="mw-redirect" title="PMID (identifier)">PMID</a> <a rel="nofollow" class="external text" href="https://pubmed.ncbi.nlm.nih.gov/33265463">33265463</a>.</cite> <span typeof="mw:File"></span> Text was copied from this source, which is available under a <a rel="nofollow" class="external text" href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International License</a>.</span>

</li>

<li id="cite_note-7"><span class="mw-cite-backlink"><b><a href="#cite_ref-7">^</a></b></span> <span class="reference-text"><cite id="CITEREFSkiera2022" class="citation book cs1">Skiera, Bernd (2022). <i>The impact of the GDPR on the online advertising market</i>. Klaus Miller, Yuxi Jin, Lennart Kraft, René Laub, Julia Schmitt. Frankfurt am Main. <a href="ISBN_(identifier)" class="mw-redirect" title="ISBN (identifier)">ISBN</a> <bdi>978-3-9824173-0-1</bdi>. <a href="OCLC_(identifier)" class="mw-redirect" title="OCLC (identifier)">OCLC</a> <a rel="nofollow" class="external text" href="https://search.worldcat.org/oclc/1303894344">1303894344</a>.</cite><span class="cs1-maint citation-comment"><code class="cs1-code">{{cite book}}</code>: CS1 maint: location missing publisher (link)</span></span>

</li>

<li id="cite_note-ITH_1-8"><span class="mw-cite-backlink"><b><a href="#cite_ref-ITH_1_8-0">^</a></b></span> <span class="reference-text"><cite class="citation web cs1"><a rel="nofollow" class="external text" href="https://edps.europa.eu/sites/edp/files/publication/19-10-30_aepd-edps_paper_hash_final_en.pdf">"Introduction to the Hash Function as a Personal Data Pseudonymisation Technique"</a> <span class="cs1-format">(PDF)</span>. Spanish Data Protection Authority. October 2019<span class="reference-accessdate">. Retrieved <span class="nowrap">31 December</span> 2023</span>.</cite></span>

</li>

<li id="cite_note-9"><span class="mw-cite-backlink"><b><a href="#cite_ref-9">^</a></b></span> <span class="reference-text"><cite id="CITEREFKolata2019" class="citation news cs1">Kolata, Gina (23 July 2019). <a rel="nofollow" class="external text" href="https://www.nytimes.com/2019/07/23/health/data-privacy-protection.html?smid=nytcore-ios-share">"Your Data Were 'Anonymized'? These Scientists Can Still Identify You"</a>. <i>The New York Times</i>.</cite></span>

</li>

<li id="cite_note-10"><span class="mw-cite-backlink"><b><a href="#cite_ref-10">^</a></b></span> <span class="reference-text"><cite class="citation web cs1 cs1-prop-foreign-lang-source"><a rel="nofollow" class="external text" href="https://www.law.co.il/computer-law/2019/07/01/nursing-companies-vs-ministry-of-defense/">"Attm (TA) 28857-06-17 Nursing Companies Association v. Ministry of Defense"</a> (in Yiddish). Pearl Cohen. 2019<span class="reference-accessdate">. Retrieved <span class="nowrap">31 December</span> 2023</span>.</cite></span>

</li>

<li id="cite_note-11"><span class="mw-cite-backlink"><b><a href="#cite_ref-11">^</a></b></span> <span class="reference-text"><cite id="CITEREFSolomon,_S.2019" class="citation web cs1">Solomon, S. (31 January 2019). <a rel="nofollow" class="external text" href="https://www.timesofisrael.com/data-is-up-for-grabs-under-outdated-israeli-privacy-law-think-tank-says">"Data is up for grabs under outdated Israeli privacy law, think tank says"</a>. <i><a href="The_Times_of_Israel" title="The Times of Israel">The Times of Israel</a></i><span class="reference-accessdate">. Retrieved <span class="nowrap">31 December</span> 2023</span>.</cite></span>

</li>

<li id="cite_note-12"><span class="mw-cite-backlink"><b><a href="#cite_ref-12">^</a></b></span> <span class="reference-text"><cite class="citation web cs1"><a rel="nofollow" class="external text" href="https://apicom.pro/dicom-de-identification/">"DICOM De-identification/Anonymization: Protecting Patient Privacy in Medical Imaging"</a>. 2024.</cite></span>

</li>

</ol></div></div>

<div class="mw-heading mw-heading2"><h2 id="Further_reading">Further reading</h2></div>

<ul><li><cite id="CITEREFRaghunathan2013" class="citation book cs1">Raghunathan, Balaji (June 2013). <i>The Complete Book of Data Anonymization: From Planning to Implementation</i>. CRC Press. <a href="ISBN_(identifier)" class="mw-redirect" title="ISBN (identifier)">ISBN</a> <bdi>9781482218565</bdi>.</cite></li>

<li><cite id="CITEREFKhaled_El_Emam,_Luk_Arbuckle2014" class="citation book cs1"><a href="Khaled_El_Emam" title="Khaled El Emam">Khaled El Emam</a>, Luk Arbuckle (August 2014). <i>Anonymizing Health Data: Case Studies and Methods to Get You Started</i>. O'Reilly Media. <a href="ISBN_(identifier)" class="mw-redirect" title="ISBN (identifier)">ISBN</a> <bdi>978-1-4493-6307-9</bdi>.</cite></li>

<li><cite id="CITEREFRolf_H._Weber,_Ulrike_I._Heinrich2012" class="citation book cs1">Rolf H. Weber, Ulrike I. Heinrich (2012). <i>Anonymization: SpringerBriefs in Cybersecurity</i>. Springer. <a href="ISBN_(identifier)" class="mw-redirect" title="ISBN (identifier)">ISBN</a> <bdi>9781447140665</bdi>.</cite></li>

<li><cite id="CITEREFAris_Gkoulalas-Divanis,_Grigorios_Loukides2012" class="citation book cs1">Aris Gkoulalas-Divanis, Grigorios Loukides (2012). <i>Anonymization of Electronic Medical Records to Support Clinical Analysis (SpringerBriefs in Electrical and Computer Engineering)</i>. Springer. <a href="ISBN_(identifier)" class="mw-redirect" title="ISBN (identifier)">ISBN</a> <bdi>9781461456674</bdi>.</cite></li>

<li><cite id="CITEREFPete_Warden" class="citation web cs1">Pete Warden. <a rel="nofollow" class="external text" href="https://web.archive.org/web/20140109052803/http://strata.oreilly.com/2011/05/anonymize-data-limits.html">"Why you can't really anonymize your data"</a>. O'Reilly Media, Inc. Archived from <a rel="nofollow" class="external text" href="http://strata.oreilly.com/2011/05/anonymize-data-limits.html">the original</a> on 9 January 2014<span class="reference-accessdate">. Retrieved <span class="nowrap">17 January</span> 2014</span>.</cite></li></ul>

<div class="mw-heading mw-heading2"><h2 id="External_links">External links</h2></div>

<ul><li>On the anonymization of Internet traffic: <a rel="nofollow" class="external text" href="http://www.caida.org/data/anonymization/index.xml">Data Sharing and Anonymization Reading List</a></li></ul></div><div><div class="zim-footer">

This article is issued from <a class="external text" title="Last edited on 2025-07-17" href="https://en.wikipedia.org/wiki/?title=Data_anonymization&oldid=1301042805">Wikipedia</a>. The text is available under <a class="external text" href="https://creativecommons.org/licenses/by-sa/4.0/deed.en">Creative Commons Attribution-Share Alike 4.0</a> unless otherwise noted. Additional terms may apply for the media files.

</div>

</div></div>

</div>

</main>

</div>

</body></html>