Effects of Age Groups and Distortion Types on Text-Based CAPTCHA Tasks
Identifieur interne : 002037 ( Istex/Corpus ); précédent : 002036; suivant : 002038Effects of Age Groups and Distortion Types on Text-Based CAPTCHA Tasks
Auteurs : Chih-Hsiang Hsu ; Ying-Lien LeeSource :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2011.
Abstract
Abstract: Completely Automatic Public Turning test to tell Computers and Humans Apart, or CAPTCHA, is a security measure that guards a system from exploitation by the discrimination between a real human being and an automated computer program via the method of presenting to the unknown user the challenges that are hard for computer yet easy for human. Focusing on text-based CAPTCHA, this study conducted an experiment to study the effect of age groups and distortion types on the CAPTCHA task. Twenty-four participants were recruited to take part in the experiment, where twelve of them were in the senior group and twelve in the young group. Participants were observed to use three general steps: recognition, rehearsal, and motor response. With the inevitability of the security measure and the increasing population of senior netizens, this study has important implications for the design of CAPTCHA systems.
Url:
DOI: 10.1007/978-3-642-21619-0_56
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Bern</OrgName><OrgAddress><City>Bern</City><Country>Switzerland</Country></OrgAddress></Affiliation><Affiliation ID="Aff9"><OrgName>Indian Institute of Technology</OrgName><OrgAddress><City>Madras</City><Country>India</Country></OrgAddress></Affiliation><Affiliation ID="Aff10"><OrgName>University of Dortmund</OrgName><OrgAddress><City>Dortmund</City><Country>Germany</Country></OrgAddress></Affiliation><Affiliation ID="Aff11"><OrgName>Massachusetts Institute of Technology</OrgName><OrgAddress><State>MA</State><Country>USA</Country></OrgAddress></Affiliation><Affiliation ID="Aff12"><OrgName>University of California</OrgName><OrgAddress><City>Los Angeles</City><State>CA</State><Country>USA</Country></OrgAddress></Affiliation><Affiliation ID="Aff13"><OrgName>University of California</OrgName><OrgAddress><City>Berkeley</City><State>CA</State><Country>USA</Country></OrgAddress></Affiliation><Affiliation ID="Aff14"><OrgName>Rice University</OrgName><OrgAddress><City>Houston</City><State>TX</State><Country>USA</Country></OrgAddress></Affiliation><Affiliation ID="Aff15"><OrgName>Max-Planck Institute of Computer Science</OrgName><OrgAddress><City>Saarbrücken</City><Country>Germany</Country></OrgAddress></Affiliation></EditorGroup></SeriesHeader><Book Language="En"><BookInfo BookProductType="Proceedings" ContainsESM="No" Language="En" MediaType="eBook" NumberingDepth="2" NumberingStyle="ContentOnly" OutputMedium="All" TocLevels="0"><BookID>978-3-642-21619-0</BookID><BookTitle>Human-Computer Interaction. Users and Applications</BookTitle><BookSubTitle>14th International Conference, HCI International 2011, Orlando, FL, USA, July 9-14, 2011, Proceedings, Part IV</BookSubTitle><BookVolumeNumber>6764</BookVolumeNumber><BookSequenceNumber>6764</BookSequenceNumber><BookDOI>10.1007/978-3-642-21619-0</BookDOI><BookTitleID>270988</BookTitleID><BookPrintISBN>978-3-642-21618-3</BookPrintISBN><BookElectronicISBN>978-3-642-21619-0</BookElectronicISBN><BookChapterCount>82</BookChapterCount><BookCopyright><CopyrightHolderName>Springer-Verlag GmbH Berlin Heidelberg</CopyrightHolderName><CopyrightYear>2011</CopyrightYear></BookCopyright><BookSubjectGroup><BookSubject Code="I" Type="Primary">Computer Science</BookSubject><BookSubject Code="I18067" Priority="1" Type="Secondary">User Interfaces and Human Computer Interaction</BookSubject><BookSubject Code="I18040" Priority="2" Type="Secondary">Information Systems Applications (incl.Internet)</BookSubject><BookSubject Code="I18059" Priority="3" Type="Secondary">Multimedia Information Systems</BookSubject><BookSubject Code="I18032" Priority="4" Type="Secondary">Information Storage and Retrieval</BookSubject><BookSubject Code="I22005" Priority="5" Type="Secondary">Computer Imaging, Vision, Pattern Recognition and Graphics</BookSubject><BookSubject Code="I26000" Priority="6" Type="Secondary">e-Commerce/e-business</BookSubject><SubjectCollection Code="SUCO11645">Computer Science</SubjectCollection></BookSubjectGroup><BookContext><SeriesID>558</SeriesID></BookContext></BookInfo><BookHeader><EditorGroup><Editor AffiliationIDS="Aff16"><EditorName DisplayOrder="Western"><GivenName>Julie</GivenName><GivenName>A.</GivenName><FamilyName>Jacko</FamilyName></EditorName><Contact><Email>jacko@umn.edu</Email></Contact></Editor><Affiliation ID="Aff16"><OrgDivision>School of Public Health, Institute of Health Informatics</OrgDivision><OrgName>University of Minnesota</OrgName><OrgAddress><Street>1260 Mayo (MMC 807), 420 Delaware Street S.E.</Street><Postcode>55455</Postcode><City>Minneapolis</City><State>MN</State><Country>USA</Country></OrgAddress></Affiliation></EditorGroup></BookHeader><Part ID="Part5"><PartInfo TocLevels="0"><PartID>5</PartID><PartNumber>Part V</PartNumber><PartSequenceNumber>5</PartSequenceNumber><PartTitle>Design and Usability Case Studies</PartTitle><PartChapterCount>14</PartChapterCount><PartContext><SeriesID>558</SeriesID><BookTitle>Human-Computer Interaction</BookTitle></PartContext></PartInfo><Chapter ID="Chap56" Language="En"><ChapterInfo ChapterType="OriginalPaper" ContainsESM="No" NumberingDepth="2" NumberingStyle="ContentOnly" TocLevels="0"><ChapterID>56</ChapterID><ChapterDOI>10.1007/978-3-642-21619-0_56</ChapterDOI><ChapterSequenceNumber>56</ChapterSequenceNumber><ChapterTitle Language="En">Effects of Age Groups and Distortion Types on Text-Based CAPTCHA Tasks</ChapterTitle><ChapterFirstPage>453</ChapterFirstPage><ChapterLastPage>455</ChapterLastPage><ChapterCopyright><CopyrightHolderName>Springer-Verlag Berlin Heidelberg</CopyrightHolderName><CopyrightYear>2011</CopyrightYear></ChapterCopyright><ChapterGrants Type="Regular"><MetadataGrant Grant="OpenAccess"></MetadataGrant><AbstractGrant Grant="OpenAccess"></AbstractGrant><BodyPDFGrant Grant="Restricted"></BodyPDFGrant><BodyHTMLGrant Grant="Restricted"></BodyHTMLGrant><BibliographyGrant Grant="Restricted"></BibliographyGrant><ESMGrant Grant="Restricted"></ESMGrant></ChapterGrants><ChapterContext><SeriesID>558</SeriesID><PartID>5</PartID><BookID>978-3-642-21619-0</BookID><BookTitle>Human-Computer Interaction</BookTitle></ChapterContext></ChapterInfo><ChapterHeader><AuthorGroup><Author AffiliationIDS="Aff17"><AuthorName DisplayOrder="Western"><GivenName>Chih-Hsiang</GivenName><FamilyName>Hsu</FamilyName></AuthorName></Author><Author AffiliationIDS="Aff17"><AuthorName DisplayOrder="Western"><GivenName>Ying-Lien</GivenName><FamilyName>Lee</FamilyName></AuthorName><Contact><Email>yinglienlee@gmail.com</Email></Contact></Author><Affiliation ID="Aff17"><OrgDivision>Department of Industrial Engineering and Management</OrgDivision><OrgName>Chaoyang University of Technology</OrgName><OrgAddress><Street>No. 168, Jifong E. Rd., Wufong Township</Street><City>Taichung County</City><Postcode>413</Postcode><Country>Taiwan</Country></OrgAddress></Affiliation></AuthorGroup><Abstract ID="Abs1" Language="En"><Heading>Abstract</Heading><Para>Completely Automatic Public Turning test to tell Computers and Humans Apart, or CAPTCHA, is a security measure that guards a system from exploitation by the discrimination between a real human being and an automated computer program via the method of presenting to the unknown user the challenges that are hard for computer yet easy for human. Focusing on text-based CAPTCHA, this study conducted an experiment to study the effect of age groups and distortion types on the CAPTCHA task. Twenty-four participants were recruited to take part in the experiment, where twelve of them were in the senior group and twelve in the young group. Participants were observed to use three general steps: recognition, rehearsal, and motor response. With the inevitability of the security measure and the increasing population of senior netizens, this study has important implications for the design of CAPTCHA systems.</Para></Abstract><KeywordGroup Language="En"><Heading>Keywords</Heading><Keyword>CAPTCHA</Keyword><Keyword>age group</Keyword><Keyword>distortion</Keyword></KeywordGroup></ChapterHeader><NoBody></NoBody></Chapter></Part></Book></Series></Publisher></istex:document></istex:metadataXml><mods version="3.6"><titleInfo lang="en"><title>Effects of Age Groups and Distortion Types on Text-Based CAPTCHA Tasks</title></titleInfo><titleInfo type="alternative" contentType="CDATA" lang="en"><title>Effects of Age Groups and Distortion Types on Text-Based CAPTCHA Tasks</title></titleInfo><name type="personal"><namePart type="given">Chih-Hsiang</namePart><namePart type="family">Hsu</namePart><affiliation>Department of Industrial Engineering and Management, Chaoyang University of Technology, No. 168, Jifong E. Rd., Wufong Township, 413, Taichung County, Taiwan</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Ying-Lien</namePart><namePart type="family">Lee</namePart><affiliation>Department of Industrial Engineering and Management, Chaoyang University of Technology, No. 168, Jifong E. Rd., Wufong Township, 413, Taichung County, Taiwan</affiliation><affiliation>E-mail: yinglienlee@gmail.com</affiliation><role><roleTerm type="text">author</roleTerm></role></name><typeOfResource>text</typeOfResource><genre type="conference [eBooks]" displayLabel="OriginalPaper"></genre><originInfo><publisher>Springer Berlin Heidelberg</publisher><place><placeTerm type="text">Berlin, Heidelberg</placeTerm></place><dateIssued encoding="w3cdtf">2011</dateIssued><copyrightDate encoding="w3cdtf">2011</copyrightDate></originInfo><language><languageTerm type="code" authority="rfc3066">en</languageTerm><languageTerm type="code" authority="iso639-2b">eng</languageTerm></language><physicalDescription><internetMediaType>text/html</internetMediaType></physicalDescription><abstract lang="en">Abstract: Completely Automatic Public Turning test to tell Computers and Humans Apart, or CAPTCHA, is a security measure that guards a system from exploitation by the discrimination between a real human being and an automated computer program via the method of presenting to the unknown user the challenges that are hard for computer yet easy for human. Focusing on text-based CAPTCHA, this study conducted an experiment to study the effect of age groups and distortion types on the CAPTCHA task. Twenty-four participants were recruited to take part in the experiment, where twelve of them were in the senior group and twelve in the young group. Participants were observed to use three general steps: recognition, rehearsal, and motor response. With the inevitability of the security measure and the increasing population of senior netizens, this study has important implications for the design of CAPTCHA systems.</abstract><relatedItem type="host"><titleInfo><title>Human-Computer Interaction. 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type="ChapterID">56</identifier><identifier type="ChapterID">Chap56</identifier><accessCondition type="use and reproduction" contentType="copyright">Springer-Verlag GmbH Berlin Heidelberg, 2011</accessCondition><recordInfo><recordContentSource>SPRINGER</recordContentSource><recordOrigin>Springer-Verlag Berlin Heidelberg, 2011</recordOrigin></recordInfo></mods></metadata><enrichments><istex:refBibTEI uri="https://api.istex.fr/document/C9D59FCF9C08AEB3FE06E2D7E67DFF74EE06FEAF/enrichments/refBib"><teiHeader></teiHeader><text><front></front><body></body><back><listBibl><biblStruct xml:id="b0"><analytic><title level="a" type="main">CAPTCHA: Using Hard AI Problems for Security</title><author><persName><forename type="first">L</forename><surname>Von Ahn</surname></persName></author></analytic><monogr><title level="m">EUROCRYPT 2003</title><editor>Biham, E.</editor><meeting><address><addrLine>Heidelberg</addrLine></address></meeting><imprint><publisher>Springer</publisher><date 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