Applying Visual Cryptography to Enhance Text Captchas

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aut.relation.endpage332
aut.relation.issue3en_NZ
aut.relation.journalMathematicsen_NZ
aut.relation.startpage332
aut.relation.volume8en_NZ
aut.researcherYan, Wei-Qi
dc.contributor.authorYan, Xen_NZ
dc.contributor.authorLiu, Fen_NZ
dc.contributor.authorYan, WQen_NZ
dc.contributor.authorLu, Yen_NZ
dc.date.accessioned2020-03-04T03:19:07Z
dc.date.available2020-03-04T03:19:07Z
dc.description.abstractNowadays, lots of applications and websites utilize text-based captchas to partially protect the authentication mechanism. However, in recent years, different ways have been exploited to automatically recognize text-based captchas especially deep learning-based ways, such as, convolutional neural network (CNN). Thus, we have to enhance the text captchas design. In this paper, using the features of the randomness for each encoding process in visual cryptography (VC) and the visual recognizability with naked human eyes, VC is applied to design and enhance text-based captcha. Experimental results using two typical deep learning-based attack models indicate the effectiveness of the designed method. By using our designed VC-enhanced text-based captcha (VCETC), the recognition rate is in some degree decreased.en_NZ
dc.identifier.citationMathematics. 2020; 8(3):332.
dc.identifier.doi10.3390/math8030332en_NZ
dc.identifier.issn2227-7390en_NZ
dc.identifier.urihttps://hdl.handle.net/10292/13187
dc.languageenen_NZ
dc.publisherMDPI AGen_NZ
dc.relation.urihttps://www.mdpi.com/2227-7390/8/3/332
dc.rightsc 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
dc.rights.accessrightsOpenAccessen_NZ
dc.subjectText captcha; Visual cryptography; Random grids; Visual cryptography application; Enhanced text captcha
dc.titleApplying Visual Cryptography to Enhance Text Captchasen_NZ
dc.typeJournal Article
pubs.elements-id371868
pubs.organisational-data/AUT
pubs.organisational-data/AUT/Design & Creative Technologies
pubs.organisational-data/AUT/Design & Creative Technologies/Engineering, Computer & Mathematical Sciences
pubs.organisational-data/AUT/PBRF
pubs.organisational-data/AUT/PBRF/PBRF Design and Creative Technologies
pubs.organisational-data/AUT/PBRF/PBRF Design and Creative Technologies/PBRF ECMS
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