Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/1135
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dc.contributor.authorBayram, Sevinç-
dc.contributor.authorSencar, Hüsrev Taha-
dc.contributor.authorMemon, Nasir-
dc.date.accessioned2019-06-26T07:40:33Z
dc.date.available2019-06-26T07:40:33Z
dc.date.issued2015-03
dc.identifier.citationBayram, S., Sencar, H. T., & Memon, N. (2015). Sensor fingerprint identification through composite fingerprints and group testing. IEEE Transactions on Information Forensics and Security, 10(3), 597-612.en_US
dc.identifier.issn1556-6013
dc.identifier.urihttps://ieeexplore.ieee.org/document/6996017-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/1135-
dc.description.abstractThe photo response non-uniformity noise associated with an imaging sensor has been shown to be a unique and persistent identifier that can be treated as the sensor's digital fingerprint. The method for attributing an image to a particular camera, however, is not suitable for source identification due to efficiency considerations, which is a one-to-many matching of a single fingerprint against a database of fingerprints. To address this problem, we propose a group-testing approach based on the notion of composite fingerprints (CFs), generated by combining many actual fingerprints together into a single fingerprint. Our technique organizes a database of fingerprints into an unordered binary search tree, wherein each internal node is represented by a fingerprint composited from all the fingerprints at the leaf nodes in the subtree beneath that node. Different search strategies are considered, and the performance is analyzed analytically and verified using numerical simulations as well as experimental results. Our results are presented in comparison with the linear search-based approach that utilizes fingerprint digests for more effective computation. Results obtained under the best achievable accuracy showed that the proposed method yields a lower overall computational cost. It is also shown that by complementary use of the fingerprint dimension reduction and CF-based search tree approaches, it is possible to further improve the search efficiency.en_US
dc.language.isoenen_US
dc.publisherIEEE-INST Electrical Electronics Engineers Inc.en_US
dc.relation.ispartofIEEE Transactions On information Forensics And Securityen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectImage Forensicsen_US
dc.subjectPhoto Response Non-Uniformity Noise (Prnu)en_US
dc.subjectSensor Fingerprint İdentificationen_US
dc.subjectEfficient Source Camera İdentificationen_US
dc.titleSensor Fingerprint Identification Through Composite Fingerprints and Group Testingen_US
dc.typeArticleen_US
dc.departmentFaculties, Faculty of Engineering, Department of Computer Engineeringen_US
dc.departmentFakülteler, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümütr_TR
dc.identifier.volume10
dc.identifier.issue3
dc.identifier.startpage597
dc.identifier.endpage612
dc.authorid0000-0001-6910-6194-
dc.identifier.wosWOS:000349671300002en_US
dc.identifier.scopus2-s2.0-84923226327en_US
dc.institutionauthorSencar, Hüsrev Taha-
dc.identifier.doi10.1109/TIFS.2014.2385634-
dc.authorscopusid8616233200-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.scopusqualityQ1-
item.openairetypeArticle-
item.languageiso639-1en-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
crisitem.author.dept02.3. Department of Computer Engineering-
Appears in Collections:Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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