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  <doc>
    <id>3076</id>
    <completedYear>2017</completedYear>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>21</pageFirst>
    <pageLast>32</pageLast>
    <pageNumber>12</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>ACM</publisherName>
    <publisherPlace>Philadelphia Pennsylvania USA</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2024-02-13</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Modeling Attacks on Photo-ID Documents and Applying Media Forensics for the Detection of Facial Morphing</title>
    <parentTitle language="eng">Konferenz: IH&amp;MMSec '17: ACM Information Hiding and Multimedia Security Workshop, 2017/ Titel: Proceedings of the 5th ACM Workshop on Information Hiding and Multimedia Security</parentTitle>
    <identifier type="isbn">978-1-4503-5061-7</identifier>
    <identifier type="url">https://dl.acm.org/doi/10.1145/3082031.3083244</identifier>
    <identifier type="doi">10.1145/3082031.3083244</identifier>
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    <licence>Creative Commons - CC BY - Namensnennung 4.0</licence>
    <author>Christian Kraetzer</author>
    <author>Andrey Makrushin</author>
    <author>Tom Neubert</author>
    <author>Mario Hildebrandt</author>
    <author>Jana Dittmann</author>
    <collection role="institutes" number="">Fachbereich Informatik und Medien</collection>
    <collection role="Hochschulbibliografie" number="1">Hochschulbibliografie</collection>
  </doc>
  <doc>
    <id>3072</id>
    <completedYear>2018</completedYear>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>49</pageFirst>
    <pageLast>54</pageLast>
    <pageNumber>6</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>ACM</publisherName>
    <publisherPlace>Innsbruck Austria</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2024-02-13</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Generalized Benford's Law for Blind Detection of Morphed Face Images</title>
    <parentTitle language="eng">Konferenz: IH&amp;MMSec '18: 6th ACM Workshop on Information Hiding and Multimedia Security, 2018/ Titel: Proceedings of the 6th ACM Workshop on Information Hiding and Multimedia Security</parentTitle>
    <identifier type="isbn">978-1-4503-5625-1</identifier>
    <identifier type="url">https://dl.acm.org/doi/10.1145/3206004.3206018</identifier>
    <identifier type="doi">10.1145/3206004.3206018</identifier>
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    <licence>Creative Commons - CC BY - Namensnennung 4.0</licence>
    <author>Andrey Makrushin</author>
    <author>Christian Kraetzer</author>
    <author>Tom Neubert</author>
    <author>Jana Dittmann</author>
    <collection role="institutes" number="">Fachbereich Informatik und Medien</collection>
    <collection role="Hochschulbibliografie" number="1">Hochschulbibliografie</collection>
  </doc>
  <doc>
    <id>3073</id>
    <completedYear>2018</completedYear>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>325</pageFirst>
    <pageLast>332</pageLast>
    <pageNumber>8</pageNumber>
    <edition/>
    <issue>Augabe: 4/ Band: 7</issue>
    <volume/>
    <type>article</type>
    <publisherName>Wiley</publisherName>
    <publisherPlace/>
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    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2024-02-13</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Extended StirTrace benchmarking of biometric and forensic qualities of morphed face images</title>
    <abstract language="eng">Since its introduction in 2014, the face morphing forgery (FMF) attack has received significant attention from the biometric and media forensic research communities. The attack aims at creating artificially weakened templates which can be successfully matched against multiple persons. If successful, the attack has an immense impact on many biometric authentication scenarios including the application of electronic machine-readable travel document (eMRTD) at automated border control gates. We extend the StirTrace framework for benchmarking FMF attacks by adding five issues: a novel three-fold definition for the quality of morphed images, a novel FMF realisation (combined morphing), a post-processing operation to simulate the digital image format used in eMRTD (passport scaling 15 kB), an automated face recognition system (VGG face descriptor) as additional means for biometric quality assessment and two feature spaces for FMF detection (keypoint features and fusion of keypoint and Benford features) as additional means for forensic quality assessment. We show that the impact of StirTrace post-processing operations on the biometric quality of morphed face images is negligible except for two noise operators and passport scaling 15 kB, the impact on the forensic quality depends on the type of post-processing, and the new FMF realisation outperforms the previously considered ones.</abstract>
    <parentTitle language="eng">IET Biometrics</parentTitle>
    <identifier type="url">https://onlinelibrary.wiley.com/doi/10.1049/iet-bmt.2017.0147</identifier>
    <identifier type="doi">10.1049/iet-bmt.2017.0147</identifier>
    <identifier type="issn">2047-4938, 2047-4946</identifier>
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    <licence>Creative Commons - CC BY - Namensnennung 4.0</licence>
    <author>Tom Neubert</author>
    <author>Andrey Makrushin</author>
    <author>Mario Hildebrandt</author>
    <author>Christian Kraetzer</author>
    <author>Jana Dittmann</author>
    <collection role="institutes" number="">Fachbereich Informatik und Medien</collection>
    <collection role="Hochschulbibliografie" number="1">Hochschulbibliografie</collection>
    <thesisPublisher>Technische Hochschule Brandenburg</thesisPublisher>
  </doc>
  <doc>
    <id>3063</id>
    <completedYear>2019</completedYear>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1</pageFirst>
    <pageLast>6</pageLast>
    <pageNumber>6</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>IEEE</publisherName>
    <publisherPlace>Delft, Netherlands</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2024-02-13</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Visual Feature Space Analyses of Face Morphing Detectors</title>
    <parentTitle language="eng">Konferenz: 2019 IEEE International Workshop on Information Forensics and Security (WIFS), Delft, Netherlands, 2019/ Konferenztitel: 2019 IEEE International Workshop on Information Forensics and Security (WIFS)</parentTitle>
    <identifier type="isbn">978-1-72813-217-4</identifier>
    <identifier type="url">https://ieeexplore.ieee.org/document/9034983/</identifier>
    <identifier type="doi">10.1109/WIFS47025.2019.9034983</identifier>
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    <licence>Creative Commons - CC BY - Namensnennung 4.0</licence>
    <author>Clemens Seibold</author>
    <author>Anna Hilsmann</author>
    <author>Andrey Makrushin</author>
    <author>Christian Kraetzer</author>
    <author>Tom Neubert</author>
    <author>Jana Dittmann</author>
    <author>Peter Eisert</author>
    <collection role="institutes" number="">Fachbereich Informatik und Medien</collection>
    <collection role="Hochschulbibliografie" number="1">Hochschulbibliografie</collection>
  </doc>
</export-example>
