Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/29993
DC FieldValueLanguage
dc.contributor.authorLeonidou, Pantelitsa-
dc.contributor.authorConstantinides, Argyris-
dc.contributor.authorBelk, Marios-
dc.contributor.authorFidas, Christos-
dc.contributor.authorPitsillides, Andreas-
dc.date.accessioned2023-07-26T11:30:11Z-
dc.date.available2023-07-26T11:30:11Z-
dc.date.issued2021-01-01-
dc.identifier.citationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)en_US
dc.identifier.isbn9783030773915-
dc.identifier.issn03029743-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/29993-
dc.description.abstractImage-recognition Human Interaction Proof (HIP) schemes are widely used security defense mechanisms that are utilized by service providers to determine whether a human user is interacting with their system and not malicious software. Inspired by recent research, which underpins the necessity for designing user-centered HIPs, this paper examines, in the frame of an accredited cognitive style theory (Field Dependence-Independence – FD-I), whether human cognitive differences in visual information processing affect users’ visual behavior when interacting with an image-recognition HIP challenge. For doing so, we conducted an eye tracking study (n = 46) in which users solved an image-recognition HIP challenge. Analysis of users’ interactions and eye gaze data revealed differences in users’ visual behavior and interactions between Holistic and Analytic users within image-recognition HIP tasks. Findings underpin the added value of considering users’ cognitive processing differences in the design of adaptive and adaptable HIP security schemes.en_US
dc.language.isoenen_US
dc.subjectEye tracking studyen_US
dc.subjectHuman cognitive differencesen_US
dc.subjectHuman interaction proof schemesen_US
dc.subjectImage-recognition CAPTCHAen_US
dc.titleEye Gaze and Interaction Differences of Holistic Versus Analytic Users in Image-Recognition Human Interaction Proof Schemesen_US
dc.typeConference Papersen_US
dc.collaborationUniversity of Cyprusen_US
dc.collaborationCognitive UX Ltden_US
dc.collaborationUniversity of Patrasen_US
dc.subject.categoryElectrical Engineering - Electronic Engineering - Information Engineeringen_US
dc.journalsSubscriptionen_US
dc.countryCyprusen_US
dc.countryGreeceen_US
dc.subject.fieldEngineering and Technologyen_US
dc.publicationPeer Revieweden_US
dc.relation.conferenceInternational Conference on HCI for Cybersecurityen_US
dc.identifier.doi10.1007/978-3-030-77392-2_5en_US
dc.identifier.scopus2-s2.0-85112180144-
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/85112180144-
dc.relation.volume12788 LNCSen_US
cut.common.academicyear2021-2022en_US
dc.identifier.spage66en_US
dc.identifier.epage75en_US
item.fulltextNo Fulltext-
item.cerifentitytypePublications-
item.grantfulltextnone-
item.openairecristypehttp://purl.org/coar/resource_type/c_c94f-
item.openairetypeconferenceObject-
item.languageiso639-1en-
crisitem.author.deptDepartment of Electrical Engineering, Computer Engineering and Informatics-
crisitem.author.facultyFaculty of Engineering and Technology-
crisitem.author.orcid0000-0002-5946-0074-
crisitem.author.parentorgFaculty of Engineering and Technology-
Appears in Collections:Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation
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