A case study for automatic detection of steganographic images in network traffic

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dc.contributor.authorErdem, Ömer
dc.contributor.authorTuran, Metin
dc.date.accessioned2020-11-21T15:56:06Z
dc.date.available2020-11-21T15:56:06Z
dc.date.issued2017en_US
dc.departmentİstanbul Ticaret Üniversitesien_US
dc.description10th International Conference on Electrical and Electronics Engineering, ELECO 2017 -- 29 November 2017 through 2 December 2017 -- -- 134351en_US
dc.description.abstractDetection and prevention of data breaches in corporate networks is one of the most important security problems of today's world. The techniques and applications proposed for solution are not successful when attackers attempt to steal data using steganography. Steganography is the art of storing data in a file called cover, such as picture, sound and video. The concealed data cannot be directly recognized in the cover. Steganalysis is the process of revealing the presence of embedded messages in these files. There are many statistical and signature based steganalysis algorithms. In this work, the detection of steganographic images with steganalysis techniques is reviewed and a system has been developed which automatically detects steganographic images in network traffic by using open source tools. © 2017 EMO (Turkish Chamber of Electrical Enginners).en_US
dc.identifier.endpage889en_US
dc.identifier.scopus2-s2.0-85046287675en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage885en_US
dc.identifier.urihttps://hdl.handle.net/11467/4090
dc.identifier.volume2018-Januaryen_US
dc.identifier.wosWOS:000426978800156en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartof2017 10th International Conference on Electrical and Electronics Engineering, ELECO 2017en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.titleA case study for automatic detection of steganographic images in network trafficen_US
dc.typeConference Objecten_US

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