Loading…
Ice and Fire: Quantifying the Risk of Re-identification and Utility in Data Anonymization
Data anonymization is required before a big-data business can run effectively without compromising the privacy of personal information it uses. It is not trivial to choose the best algorithm to anonymize some given data securely for a given purpose. In accurately assessing the risk of data being com...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Conference Proceeding |
| Language: | English |
| Subjects: | |
| Online Access: | Request full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| cited_by | |
|---|---|
| cites | |
| container_end_page | 1042 |
| container_issue | |
| container_start_page | 1035 |
| container_title | |
| container_volume | |
| creator | Kikuchi, Hiroaki Yamaguchi, Takayasu Hamada, Koki Yamaoka, Yuji Oguri, Hidenobu Sakuma, Jun |
| description | Data anonymization is required before a big-data business can run effectively without compromising the privacy of personal information it uses. It is not trivial to choose the best algorithm to anonymize some given data securely for a given purpose. In accurately assessing the risk of data being compromised, there needs to be a balance between utility and security. Therefore, using common pseudo microdata, we propose a competition for the best anonymization and re-identification algorithm. The paper addresses the aim of the competition, the target microdata, sample algorithms, utility and security metrics. The design of an evaluation platform is also considered. |
| doi_str_mv | 10.1109/AINA.2016.151 |
| format | conference_proceeding |
| fullrecord | <record><control><sourceid>proquest_CHZPO</sourceid><recordid>TN_cdi_proquest_miscellaneous_1816091193</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>7474203</ieee_id><sourcerecordid>1816091193</sourcerecordid><originalsourceid>FETCH-LOGICAL-i274t-fb66a14a9d53e54405244ff87c36a83d994ac0c704c2bf10a823e7e85a22c5233</originalsourceid><addsrcrecordid>eNotjz1PwzAYhA0CiVI6MrF4ZEnxZ2yzRUChUgWiohJMkes48ELqlNgdwq-Htkw33POcdAidUzKmlJirYvpYjBmh-ZhKeoBGRmkqiSFUSyUO0YBxzjKZS32EBlRKkgkhX0_QaYyfhPBcKDlAb1PnsQ0VnkDnr_HzxoYEdQ_hHacPj-cQv3Bb47nPoPLbCpxN0Iads0jQQOoxBHxrk8VFaEO_gp8dcYaOa9tEP_rPIVpM7l5uHrLZ0_30pphlwJRIWb3Mc0uFNZXkXgpBJBOirrVyPLeaV8YI64hTRDi2rCmxmnGvvJaWMSf_Lg7R5X533bXfGx9TuYLofNPY4NtNLKmmOTGUmi16sUfBe1-uO1jZri-VUIIRzn8Bf3JgRw</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype><pqid>1816091193</pqid></control><display><type>conference_proceeding</type><title>Ice and Fire: Quantifying the Risk of Re-identification and Utility in Data Anonymization</title><source>IEEE Xplore All Conference Series</source><creator>Kikuchi, Hiroaki ; Yamaguchi, Takayasu ; Hamada, Koki ; Yamaoka, Yuji ; Oguri, Hidenobu ; Sakuma, Jun</creator><creatorcontrib>Kikuchi, Hiroaki ; Yamaguchi, Takayasu ; Hamada, Koki ; Yamaoka, Yuji ; Oguri, Hidenobu ; Sakuma, Jun</creatorcontrib><description>Data anonymization is required before a big-data business can run effectively without compromising the privacy of personal information it uses. It is not trivial to choose the best algorithm to anonymize some given data securely for a given purpose. In accurately assessing the risk of data being compromised, there needs to be a balance between utility and security. Therefore, using common pseudo microdata, we propose a competition for the best anonymization and re-identification algorithm. The paper addresses the aim of the competition, the target microdata, sample algorithms, utility and security metrics. The design of an evaluation platform is also considered.</description><identifier>ISSN: 1550-445X</identifier><identifier>EISSN: 2332-5658</identifier><identifier>EISBN: 9781509018574</identifier><identifier>EISBN: 1509018573</identifier><identifier>EISBN: 9781509018581</identifier><identifier>EISBN: 1509018581</identifier><identifier>DOI: 10.1109/AINA.2016.151</identifier><identifier>CODEN: IEEPAD</identifier><language>eng</language><publisher>IEEE</publisher><subject>Algorithms ; anonymity ; Business ; Competition ; Conferences ; Data privacy ; Fires ; Ice ; Indexes ; k-anonymity ; Laboratories ; Measurement ; Platforms ; quantification ; re-identified risk ; Risk ; Security ; Utilities</subject><ispartof>2016 IEEE 30th International Conference on Advanced Information Networking and Applications (AINA), 2016, p.1035-1042</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/7474203$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,314,780,784,789,790,27924,27925,54555,54932</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/7474203$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Kikuchi, Hiroaki</creatorcontrib><creatorcontrib>Yamaguchi, Takayasu</creatorcontrib><creatorcontrib>Hamada, Koki</creatorcontrib><creatorcontrib>Yamaoka, Yuji</creatorcontrib><creatorcontrib>Oguri, Hidenobu</creatorcontrib><creatorcontrib>Sakuma, Jun</creatorcontrib><title>Ice and Fire: Quantifying the Risk of Re-identification and Utility in Data Anonymization</title><title>2016 IEEE 30th International Conference on Advanced Information Networking and Applications (AINA)</title><addtitle>AINA</addtitle><description>Data anonymization is required before a big-data business can run effectively without compromising the privacy of personal information it uses. It is not trivial to choose the best algorithm to anonymize some given data securely for a given purpose. In accurately assessing the risk of data being compromised, there needs to be a balance between utility and security. Therefore, using common pseudo microdata, we propose a competition for the best anonymization and re-identification algorithm. The paper addresses the aim of the competition, the target microdata, sample algorithms, utility and security metrics. The design of an evaluation platform is also considered.</description><subject>Algorithms</subject><subject>anonymity</subject><subject>Business</subject><subject>Competition</subject><subject>Conferences</subject><subject>Data privacy</subject><subject>Fires</subject><subject>Ice</subject><subject>Indexes</subject><subject>k-anonymity</subject><subject>Laboratories</subject><subject>Measurement</subject><subject>Platforms</subject><subject>quantification</subject><subject>re-identified risk</subject><subject>Risk</subject><subject>Security</subject><subject>Utilities</subject><issn>1550-445X</issn><issn>2332-5658</issn><isbn>9781509018574</isbn><isbn>1509018573</isbn><isbn>9781509018581</isbn><isbn>1509018581</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2016</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNotjz1PwzAYhA0CiVI6MrF4ZEnxZ2yzRUChUgWiohJMkes48ELqlNgdwq-Htkw33POcdAidUzKmlJirYvpYjBmh-ZhKeoBGRmkqiSFUSyUO0YBxzjKZS32EBlRKkgkhX0_QaYyfhPBcKDlAb1PnsQ0VnkDnr_HzxoYEdQ_hHacPj-cQv3Bb47nPoPLbCpxN0Iads0jQQOoxBHxrk8VFaEO_gp8dcYaOa9tEP_rPIVpM7l5uHrLZ0_30pphlwJRIWb3Mc0uFNZXkXgpBJBOirrVyPLeaV8YI64hTRDi2rCmxmnGvvJaWMSf_Lg7R5X533bXfGx9TuYLofNPY4NtNLKmmOTGUmi16sUfBe1-uO1jZri-VUIIRzn8Bf3JgRw</recordid><startdate>20160301</startdate><enddate>20160301</enddate><creator>Kikuchi, Hiroaki</creator><creator>Yamaguchi, Takayasu</creator><creator>Hamada, Koki</creator><creator>Yamaoka, Yuji</creator><creator>Oguri, Hidenobu</creator><creator>Sakuma, Jun</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>20160301</creationdate><title>Ice and Fire: Quantifying the Risk of Re-identification and Utility in Data Anonymization</title><author>Kikuchi, Hiroaki ; Yamaguchi, Takayasu ; Hamada, Koki ; Yamaoka, Yuji ; Oguri, Hidenobu ; Sakuma, Jun</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i274t-fb66a14a9d53e54405244ff87c36a83d994ac0c704c2bf10a823e7e85a22c5233</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Algorithms</topic><topic>anonymity</topic><topic>Business</topic><topic>Competition</topic><topic>Conferences</topic><topic>Data privacy</topic><topic>Fires</topic><topic>Ice</topic><topic>Indexes</topic><topic>k-anonymity</topic><topic>Laboratories</topic><topic>Measurement</topic><topic>Platforms</topic><topic>quantification</topic><topic>re-identified risk</topic><topic>Risk</topic><topic>Security</topic><topic>Utilities</topic><toplevel>online_resources</toplevel><creatorcontrib>Kikuchi, Hiroaki</creatorcontrib><creatorcontrib>Yamaguchi, Takayasu</creatorcontrib><creatorcontrib>Hamada, Koki</creatorcontrib><creatorcontrib>Yamaoka, Yuji</creatorcontrib><creatorcontrib>Oguri, Hidenobu</creatorcontrib><creatorcontrib>Sakuma, Jun</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Kikuchi, Hiroaki</au><au>Yamaguchi, Takayasu</au><au>Hamada, Koki</au><au>Yamaoka, Yuji</au><au>Oguri, Hidenobu</au><au>Sakuma, Jun</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Ice and Fire: Quantifying the Risk of Re-identification and Utility in Data Anonymization</atitle><btitle>2016 IEEE 30th International Conference on Advanced Information Networking and Applications (AINA)</btitle><stitle>AINA</stitle><date>2016-03-01</date><risdate>2016</risdate><spage>1035</spage><epage>1042</epage><pages>1035-1042</pages><issn>1550-445X</issn><eissn>2332-5658</eissn><eisbn>9781509018574</eisbn><eisbn>1509018573</eisbn><eisbn>9781509018581</eisbn><eisbn>1509018581</eisbn><coden>IEEPAD</coden><abstract>Data anonymization is required before a big-data business can run effectively without compromising the privacy of personal information it uses. It is not trivial to choose the best algorithm to anonymize some given data securely for a given purpose. In accurately assessing the risk of data being compromised, there needs to be a balance between utility and security. Therefore, using common pseudo microdata, we propose a competition for the best anonymization and re-identification algorithm. The paper addresses the aim of the competition, the target microdata, sample algorithms, utility and security metrics. The design of an evaluation platform is also considered.</abstract><pub>IEEE</pub><doi>10.1109/AINA.2016.151</doi><tpages>8</tpages></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | ISSN: 1550-445X |
| ispartof | 2016 IEEE 30th International Conference on Advanced Information Networking and Applications (AINA), 2016, p.1035-1042 |
| issn | 1550-445X 2332-5658 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_1816091193 |
| source | IEEE Xplore All Conference Series |
| subjects | Algorithms anonymity Business Competition Conferences Data privacy Fires Ice Indexes k-anonymity Laboratories Measurement Platforms quantification re-identified risk Risk Security Utilities |
| title | Ice and Fire: Quantifying the Risk of Re-identification and Utility in Data Anonymization |
| url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-20T14%3A33%3A37IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_CHZPO&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Ice%20and%20Fire:%20Quantifying%20the%20Risk%20of%20Re-identification%20and%20Utility%20in%20Data%20Anonymization&rft.btitle=2016%20IEEE%2030th%20International%20Conference%20on%20Advanced%20Information%20Networking%20and%20Applications%20(AINA)&rft.au=Kikuchi,%20Hiroaki&rft.date=2016-03-01&rft.spage=1035&rft.epage=1042&rft.pages=1035-1042&rft.issn=1550-445X&rft.eissn=2332-5658&rft.coden=IEEPAD&rft_id=info:doi/10.1109/AINA.2016.151&rft.eisbn=9781509018574&rft.eisbn_list=1509018573&rft.eisbn_list=9781509018581&rft.eisbn_list=1509018581&rft_dat=%3Cproquest_CHZPO%3E1816091193%3C/proquest_CHZPO%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-i274t-fb66a14a9d53e54405244ff87c36a83d994ac0c704c2bf10a823e7e85a22c5233%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=1816091193&rft_id=info:pmid/&rft_ieee_id=7474203&rfr_iscdi=true |