ANALYZING FACIAL RECOGNITION DATA AND SOCIAL NETWORK DATA FOR USER AUTHENTICATION
Tools, strategies, and techniques are provided for evaluating the identities of different entities to protect business enterprises, consumers, and other entities from fraud by combining biometric activity data with facial recognition data for end users. Risks associated with various entities can be...
Gespeichert in:
| Hauptverfasser: | , , |
|---|---|
| Format: | Patent |
| Sprache: | eng |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | |
|---|---|
| container_issue | |
| container_start_page | |
| container_title | |
| container_volume | |
| creator | KAMERMAN, Justin LI, Xinyu MADHU, Sunil |
| description | Tools, strategies, and techniques are provided for evaluating the identities of different entities to protect business enterprises, consumers, and other entities from fraud by combining biometric activity data with facial recognition data for end users. Risks associated with various entities can be analyzed and assessed based on a combination of user liveliness check data, facial image data, social network data, and/or professional network data, among other data sources. In various embodiments, the risk assessment may include calculating an authorization score or authenticity score based on different portions or combinations of the collected and processed data. |
| format | Patent |
| fullrecord | <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_SG10201913318YA</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>SG10201913318YA</sourcerecordid><originalsourceid>FETCH-epo_espacenet_SG10201913318YA3</originalsourceid><addsrcrecordid>eNrjZAh09HP0iYzy9HNXcHN09nT0UQhydfZ39_MM8fT3U3BxDHFUcPRzUQj2B8v5uYaE-wd5Q8Td_IMUQoNdgxQcQ0M8XP1CPJ0dQZp4GFjTEnOKU3mhNDeDiptriLOHbmpBfnxqcUFicmpeakl8sLuhgZGBoaWhsbGhRaSjMZHKAK7QMLw</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>ANALYZING FACIAL RECOGNITION DATA AND SOCIAL NETWORK DATA FOR USER AUTHENTICATION</title><source>esp@cenet</source><creator>KAMERMAN, Justin ; LI, Xinyu ; MADHU, Sunil</creator><creatorcontrib>KAMERMAN, Justin ; LI, Xinyu ; MADHU, Sunil</creatorcontrib><description>Tools, strategies, and techniques are provided for evaluating the identities of different entities to protect business enterprises, consumers, and other entities from fraud by combining biometric activity data with facial recognition data for end users. Risks associated with various entities can be analyzed and assessed based on a combination of user liveliness check data, facial image data, social network data, and/or professional network data, among other data sources. In various embodiments, the risk assessment may include calculating an authorization score or authenticity score based on different portions or combinations of the collected and processed data.</description><language>eng</language><creationdate>2020</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20200227&DB=EPODOC&CC=SG&NR=10201913318YA$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,776,881,25542,76289</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20200227&DB=EPODOC&CC=SG&NR=10201913318YA$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>KAMERMAN, Justin</creatorcontrib><creatorcontrib>LI, Xinyu</creatorcontrib><creatorcontrib>MADHU, Sunil</creatorcontrib><title>ANALYZING FACIAL RECOGNITION DATA AND SOCIAL NETWORK DATA FOR USER AUTHENTICATION</title><description>Tools, strategies, and techniques are provided for evaluating the identities of different entities to protect business enterprises, consumers, and other entities from fraud by combining biometric activity data with facial recognition data for end users. Risks associated with various entities can be analyzed and assessed based on a combination of user liveliness check data, facial image data, social network data, and/or professional network data, among other data sources. In various embodiments, the risk assessment may include calculating an authorization score or authenticity score based on different portions or combinations of the collected and processed data.</description><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2020</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZAh09HP0iYzy9HNXcHN09nT0UQhydfZ39_MM8fT3U3BxDHFUcPRzUQj2B8v5uYaE-wd5Q8Td_IMUQoNdgxQcQ0M8XP1CPJ0dQZp4GFjTEnOKU3mhNDeDiptriLOHbmpBfnxqcUFicmpeakl8sLuhgZGBoaWhsbGhRaSjMZHKAK7QMLw</recordid><startdate>20200227</startdate><enddate>20200227</enddate><creator>KAMERMAN, Justin</creator><creator>LI, Xinyu</creator><creator>MADHU, Sunil</creator><scope>EVB</scope></search><sort><creationdate>20200227</creationdate><title>ANALYZING FACIAL RECOGNITION DATA AND SOCIAL NETWORK DATA FOR USER AUTHENTICATION</title><author>KAMERMAN, Justin ; LI, Xinyu ; MADHU, Sunil</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_SG10201913318YA3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng</language><creationdate>2020</creationdate><toplevel>online_resources</toplevel><creatorcontrib>KAMERMAN, Justin</creatorcontrib><creatorcontrib>LI, Xinyu</creatorcontrib><creatorcontrib>MADHU, Sunil</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>KAMERMAN, Justin</au><au>LI, Xinyu</au><au>MADHU, Sunil</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>ANALYZING FACIAL RECOGNITION DATA AND SOCIAL NETWORK DATA FOR USER AUTHENTICATION</title><date>2020-02-27</date><risdate>2020</risdate><abstract>Tools, strategies, and techniques are provided for evaluating the identities of different entities to protect business enterprises, consumers, and other entities from fraud by combining biometric activity data with facial recognition data for end users. Risks associated with various entities can be analyzed and assessed based on a combination of user liveliness check data, facial image data, social network data, and/or professional network data, among other data sources. In various embodiments, the risk assessment may include calculating an authorization score or authenticity score based on different portions or combinations of the collected and processed data.</abstract><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | |
| ispartof | |
| issn | |
| language | eng |
| recordid | cdi_epo_espacenet_SG10201913318YA |
| source | esp@cenet |
| title | ANALYZING FACIAL RECOGNITION DATA AND SOCIAL NETWORK DATA FOR USER AUTHENTICATION |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-08T21%3A35%3A54IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-epo_EVB&rft_val_fmt=info:ofi/fmt:kev:mtx:patent&rft.genre=patent&rft.au=KAMERMAN,%20Justin&rft.date=2020-02-27&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3ESG10201913318YA%3C/epo_EVB%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true |