What to Consider When Considering Differential Privacy for Policy
Differential privacy (DP) is a mathematical definition of privacy that can be widely applied when publishing data. DP has been recognized as a potential means of adhering to various privacy-related legal requirements. However, it can be difficult to reason about whether DP may be appropriate for a g...
Gespeichert in:
Veröffentlicht in: | Policy insights from the behavioral and brain sciences 2024-10, Vol.11 (2), p.132-140 |
---|---|
Hauptverfasser: | , |
Format: | Artikel |
Sprache: | eng |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 140 |
---|---|
container_issue | 2 |
container_start_page | 132 |
container_title | Policy insights from the behavioral and brain sciences |
container_volume | 11 |
creator | Nanayakkara, Priyanka Hullman, Jessica |
description | Differential privacy (DP) is a mathematical definition of privacy that can be widely applied when publishing data. DP has been recognized as a potential means of adhering to various privacy-related legal requirements. However, it can be difficult to reason about whether DP may be appropriate for a given context due to tensions that arise when it is brought from theory into practice. To aid policymaking around privacy concerns, we identify three categories of challenges to understanding DP along with associated questions that policymakers can ask about the potential deployment context to anticipate its impacts. |
doi_str_mv | 10.1177/23727322241278687 |
format | Article |
fullrecord | <record><control><sourceid>sage_cross</sourceid><recordid>TN_cdi_crossref_primary_10_1177_23727322241278687</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sage_id>10.1177_23727322241278687</sage_id><sourcerecordid>10.1177_23727322241278687</sourcerecordid><originalsourceid>FETCH-LOGICAL-c166t-4327b3f4c2dec42e9b49ec205736dd71df4a22256811335df9bf31dd4b6d35693</originalsourceid><addsrcrecordid>eNp9kM1qwzAQhEVpoSHNA_SmF3Cq1cqSfQzuLwSaQ0uORtZPouDaRXILfvs6pORS6Gl3B75lZgi5BbYEUOqOo-IKOecCuCpkoS7I7KhlCpFdnnfOr8kipQNjDPJSARYzstru9UCHnlZ9l4J1kW73rjtfodvR--C9i64bgm7pJoZvbUbq-0g3fRvMeEOuvG6TW_zOOXl_fHirnrP169NLtVpnBqQcMoFcNeiF4dYZwV3ZiNIZznKF0loF1gs9JchlAYCYW182HsFa0UiLuSxxTuD018Q-peh8_RnDh45jDaw-1lD_qWFilicm6Z2rD_1X7CaL_wA_cBNb4Q</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>What to Consider When Considering Differential Privacy for Policy</title><source>SAGE Complete</source><creator>Nanayakkara, Priyanka ; Hullman, Jessica</creator><creatorcontrib>Nanayakkara, Priyanka ; Hullman, Jessica</creatorcontrib><description>Differential privacy (DP) is a mathematical definition of privacy that can be widely applied when publishing data. DP has been recognized as a potential means of adhering to various privacy-related legal requirements. However, it can be difficult to reason about whether DP may be appropriate for a given context due to tensions that arise when it is brought from theory into practice. To aid policymaking around privacy concerns, we identify three categories of challenges to understanding DP along with associated questions that policymakers can ask about the potential deployment context to anticipate its impacts.</description><identifier>ISSN: 2372-7322</identifier><identifier>EISSN: 2372-7330</identifier><identifier>DOI: 10.1177/23727322241278687</identifier><language>eng</language><publisher>Los Angeles, CA: SAGE Publications</publisher><ispartof>Policy insights from the behavioral and brain sciences, 2024-10, Vol.11 (2), p.132-140</ispartof><rights>The Author(s) 2024</rights><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c166t-4327b3f4c2dec42e9b49ec205736dd71df4a22256811335df9bf31dd4b6d35693</cites><orcidid>0000-0002-0597-6657</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://journals.sagepub.com/doi/pdf/10.1177/23727322241278687$$EPDF$$P50$$Gsage$$H</linktopdf><linktohtml>$$Uhttps://journals.sagepub.com/doi/10.1177/23727322241278687$$EHTML$$P50$$Gsage$$H</linktohtml><link.rule.ids>314,776,780,21798,27901,27902,43597,43598</link.rule.ids></links><search><creatorcontrib>Nanayakkara, Priyanka</creatorcontrib><creatorcontrib>Hullman, Jessica</creatorcontrib><title>What to Consider When Considering Differential Privacy for Policy</title><title>Policy insights from the behavioral and brain sciences</title><description>Differential privacy (DP) is a mathematical definition of privacy that can be widely applied when publishing data. DP has been recognized as a potential means of adhering to various privacy-related legal requirements. However, it can be difficult to reason about whether DP may be appropriate for a given context due to tensions that arise when it is brought from theory into practice. To aid policymaking around privacy concerns, we identify three categories of challenges to understanding DP along with associated questions that policymakers can ask about the potential deployment context to anticipate its impacts.</description><issn>2372-7322</issn><issn>2372-7330</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNp9kM1qwzAQhEVpoSHNA_SmF3Cq1cqSfQzuLwSaQ0uORtZPouDaRXILfvs6pORS6Gl3B75lZgi5BbYEUOqOo-IKOecCuCpkoS7I7KhlCpFdnnfOr8kipQNjDPJSARYzstru9UCHnlZ9l4J1kW73rjtfodvR--C9i64bgm7pJoZvbUbq-0g3fRvMeEOuvG6TW_zOOXl_fHirnrP169NLtVpnBqQcMoFcNeiF4dYZwV3ZiNIZznKF0loF1gs9JchlAYCYW182HsFa0UiLuSxxTuD018Q-peh8_RnDh45jDaw-1lD_qWFilicm6Z2rD_1X7CaL_wA_cBNb4Q</recordid><startdate>202410</startdate><enddate>202410</enddate><creator>Nanayakkara, Priyanka</creator><creator>Hullman, Jessica</creator><general>SAGE Publications</general><scope>AAYXX</scope><scope>CITATION</scope><orcidid>https://orcid.org/0000-0002-0597-6657</orcidid></search><sort><creationdate>202410</creationdate><title>What to Consider When Considering Differential Privacy for Policy</title><author>Nanayakkara, Priyanka ; Hullman, Jessica</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c166t-4327b3f4c2dec42e9b49ec205736dd71df4a22256811335df9bf31dd4b6d35693</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><toplevel>online_resources</toplevel><creatorcontrib>Nanayakkara, Priyanka</creatorcontrib><creatorcontrib>Hullman, Jessica</creatorcontrib><collection>CrossRef</collection><jtitle>Policy insights from the behavioral and brain sciences</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Nanayakkara, Priyanka</au><au>Hullman, Jessica</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>What to Consider When Considering Differential Privacy for Policy</atitle><jtitle>Policy insights from the behavioral and brain sciences</jtitle><date>2024-10</date><risdate>2024</risdate><volume>11</volume><issue>2</issue><spage>132</spage><epage>140</epage><pages>132-140</pages><issn>2372-7322</issn><eissn>2372-7330</eissn><abstract>Differential privacy (DP) is a mathematical definition of privacy that can be widely applied when publishing data. DP has been recognized as a potential means of adhering to various privacy-related legal requirements. However, it can be difficult to reason about whether DP may be appropriate for a given context due to tensions that arise when it is brought from theory into practice. To aid policymaking around privacy concerns, we identify three categories of challenges to understanding DP along with associated questions that policymakers can ask about the potential deployment context to anticipate its impacts.</abstract><cop>Los Angeles, CA</cop><pub>SAGE Publications</pub><doi>10.1177/23727322241278687</doi><tpages>9</tpages><orcidid>https://orcid.org/0000-0002-0597-6657</orcidid></addata></record> |
fulltext | fulltext |
identifier | ISSN: 2372-7322 |
ispartof | Policy insights from the behavioral and brain sciences, 2024-10, Vol.11 (2), p.132-140 |
issn | 2372-7322 2372-7330 |
language | eng |
recordid | cdi_crossref_primary_10_1177_23727322241278687 |
source | SAGE Complete |
title | What to Consider When Considering Differential Privacy for Policy |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-03T18%3A15%3A24IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-sage_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=What%20to%20Consider%20When%20Considering%20Differential%20Privacy%20for%20Policy&rft.jtitle=Policy%20insights%20from%20the%20behavioral%20and%20brain%20sciences&rft.au=Nanayakkara,%20Priyanka&rft.date=2024-10&rft.volume=11&rft.issue=2&rft.spage=132&rft.epage=140&rft.pages=132-140&rft.issn=2372-7322&rft.eissn=2372-7330&rft_id=info:doi/10.1177/23727322241278687&rft_dat=%3Csage_cross%3E10.1177_23727322241278687%3C/sage_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rft_sage_id=10.1177_23727322241278687&rfr_iscdi=true |