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dc.contributor.authorLerch Hostalot, Daniel-
dc.contributor.authorMegías Jiménez, David-
dc.contributor.otherUniversitat Oberta de Catalunya. Internet Interdisciplinary Institute (IN3)-
dc.date.accessioned2019-09-23T11:18:35Z-
dc.date.available2019-09-23T11:18:35Z-
dc.date.issued2019-09-
dc.identifier.citationLerch-Hostalot, D. & Megías, D. (2019). Detection of classifier inconsistencies in image steganalysis. 7th ACM Workshop on Information Hiding and Multimedia Security. Proceedings, 2019 (), 222-229. doi: 10.1145/3335203.3335738-
dc.identifier.isbn9781450368216-
dc.identifier.urihttp://hdl.handle.net/10609/100966-
dc.description.abstractIn this paper, a methodology to detect inconsistencies in classification-based image steganalysis is presented. The proposed approach uses two classifiers: the usual one, trained with a set formed by cover and stego images, and a second classifier trained with the set obtained after embedding additional random messages into the original training set. When the decisions of these two classifiers are not consistent, we know that the prediction is not reliable. The number of inconsistencies in the predictions of a testing set may indicate that the classifier is not performing correctly in the testing scenario. This occurs, for example, in case of cover source mismatch, or when we are trying to detect a steganographic method that the classifier is no capable of modelling accurately. We also show how the number of inconsistencies can be used to predict the reliability of the classifier (classification errors).en
dc.format.mimetypeapplication/pdf-
dc.language.isoeng-
dc.publisher7th ACM Workshop on Information Hiding and Multimedia Security. Proceedings-
dc.relation.ispartof7th ACM Workshop on Information Hiding and Multimedia Security. Proceedings, 2019-
dc.relation.ispartofseries7th ACM Workshop on Information Hiding and Multimedia Security, Paris, França, 3-5, juliol, 2019-
dc.rightsCC BY-NC-ND-
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/-
dc.subjectsteganalysisen
dc.subjectcover source mismatchen
dc.subjectmachine learningen
dc.subjectestegoanálisises
dc.subjectestegoanàlisica
dc.subjectaprenentatge automàticca
dc.subjectaprendizaje automáticoes
dc.subjectdesajustament de la font de portadaca
dc.subjectdesajuste de la fuente de portadaes
dc.subject.lcshComputer securityen
dc.titleDetection of classifier inconsistencies in image steganalysis-
dc.typeinfo:eu-repo/semantics/conferenceObject-
dc.subject.lemacSeguretat informàticaca
dc.subject.lcshesSeguridad informáticaes
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess-
dc.identifier.doi10.1145/3335203.3335738-
dc.relation.projectIDinfo:eu-repo/grantAgreement/RTI2018-095094-B-C22-
dc.relation.projectIDinfo:eu-repo/grantAgreement/TIN2014-57364-C2-2-R-
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