@inproceedings{KraetzerMakrushinNeubertetal.2017, author = {Kraetzer, Christian and Makrushin, Andrey and Neubert, Tom and Hildebrandt, Mario and Dittmann, Jana}, title = {Modeling Attacks on Photo-ID Documents and Applying Media Forensics for the Detection of Facial Morphing}, series = {Konferenz: IH\&MMSec '17: ACM Information Hiding and Multimedia Security Workshop, 2017/ Titel: Proceedings of the 5th ACM Workshop on Information Hiding and Multimedia Security}, booktitle = {Konferenz: IH\&MMSec '17: ACM Information Hiding and Multimedia Security Workshop, 2017/ Titel: Proceedings of the 5th ACM Workshop on Information Hiding and Multimedia Security}, publisher = {ACM}, address = {Philadelphia Pennsylvania USA}, isbn = {978-1-4503-5061-7}, doi = {10.1145/3082031.3083244}, pages = {21 -- 32}, year = {2017}, language = {en} } @inproceedings{HildebrandtNeubertMakrushinetal.2017, author = {Hildebrandt, Mario and Neubert, Tom and Makrushin, Andrey and Dittmann, Jana}, title = {Benchmarking face morphing forgery detection: Application of stirtrace for impact simulation of different processing steps}, series = {Konferenz: 2017 5th International Workshop on Biometrics and Forensics (IWBF), 2017/ Titel: 2017 5th International Workshop on Biometrics and Forensics (IWBF)}, booktitle = {Konferenz: 2017 5th International Workshop on Biometrics and Forensics (IWBF), 2017/ Titel: 2017 5th International Workshop on Biometrics and Forensics (IWBF)}, publisher = {IEEE}, address = {Coventry, United Kingdom}, isbn = {978-1-5090-5791-7}, doi = {10.1109/IWBF.2017.7935087}, pages = {1 -- 6}, year = {2017}, abstract = {We analyze StirTrace towards benchmarking face morphing forgeries and extending it by additional scaling functions for the face biometrics scenario. We benchmark a Benford's law based multi-compression-anomaly detection approach and acceptance rates of morphs for a face matcher to determine the impact of the processing on the quality of the forgeries. We use 2 different approaches for automatically creating 3940 images of morphed faces. Based on this data set, 86614 images are created using StirTrace. A manual selection of 183 high quality morphs is used to derive tendencies based on the subjective forgery quality. Our results show that the anomaly detection seems to be able to detect anomalies in the morphing regions, the multi-compression-anomaly detection performance after the processing can be differentiated into good (e.g. cropping), partially critical (e.g. rotation) and critical results (e.g. additive noise). The influence of the processing on the biometric matcher is marginal.}, language = {en} } @inproceedings{MakrushinKraetzerNeubertetal.2018, author = {Makrushin, Andrey and Kraetzer, Christian and Neubert, Tom and Dittmann, Jana}, title = {Generalized Benford's Law for Blind Detection of Morphed Face Images}, series = {Konferenz: IH\&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}, booktitle = {Konferenz: IH\&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}, publisher = {ACM}, address = {Innsbruck Austria}, isbn = {978-1-4503-5625-1}, doi = {10.1145/3206004.3206018}, pages = {49 -- 54}, year = {2018}, language = {en} } @article{NeubertMakrushinHildebrandtetal.2018, author = {Neubert, Tom and Makrushin, Andrey and Hildebrandt, Mario and Kraetzer, Christian and Dittmann, Jana}, title = {Extended StirTrace benchmarking of biometric and forensic qualities of morphed face images}, series = {IET Biometrics}, journal = {IET Biometrics}, number = {Augabe: 4/ Band: 7}, publisher = {Wiley}, issn = {2047-4938, 2047-4946}, doi = {10.1049/iet-bmt.2017.0147}, pages = {325 -- 332}, year = {2018}, abstract = {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.}, language = {en} } @inproceedings{MakrushinNeubertDittmann2017, author = {Makrushin, Andrey and Neubert, Tom and Dittmann, Jana}, title = {Automatic Generation and Detection of Visually Faultless Facial Morphs}, series = {Konferenz: International Conference on Computer Vision Theory and Applications, 2017/ Titel: Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications}, booktitle = {Konferenz: International Conference on Computer Vision Theory and Applications, 2017/ Titel: Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications}, publisher = {SCITEPRESS - Science and Technology Publications}, address = {Porto, Portugal}, isbn = {978-989-758-225-7 978-989-758-226-4 978-989-758-227-1}, doi = {10.5220/0006131100390050}, pages = {39 -- 50}, year = {2017}, abstract = {This paper introduces an approach to automatic generation of visually faultless facial morphs along with a proposal on how such morphs can be automatically detected. It is endeavored that the created morphs cannot be recognized as such with the naked eye and a reference automatic face recognition (AFR) system produces high similarity scores while matching a morph against faces of persons who participated in morphing. Automatic generation of morphs allows for creating abundant experimental data, which is essential (i) for evaluating the performance of AFR systems to reject morphs and (ii) for training forensic systems to detect morphs. Our first experiment shows that human performance to distinguish between morphed and genuine face images is close to random guessing. In our second experiment, the reference AFR system has verified 11.78\% of morphs against any of genuine images at the decision threshold of 1\% false acceptance rate. These results indicate that facial morphing is a serious threat to access control systems aided by AFR and establish the need for morph detection approaches. Our third experiment shows that the distribution of Benford features extracted from quantized DCT coefficients of JPEG-compressed morphs is substantially different from that of genuine images enabling the automatic detection of morphs.}, language = {en} } @inproceedings{SeiboldHilsmannMakrushinetal.2019, author = {Seibold, Clemens and Hilsmann, Anna and Makrushin, Andrey and Kraetzer, Christian and Neubert, Tom and Dittmann, Jana and Eisert, Peter}, title = {Visual Feature Space Analyses of Face Morphing Detectors}, series = {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)}, booktitle = {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)}, publisher = {IEEE}, address = {Delft, Netherlands}, isbn = {978-1-72813-217-4}, doi = {10.1109/WIFS47025.2019.9034983}, pages = {1 -- 6}, year = {2019}, language = {en} } @inproceedings{MakrushinNeubertDittmann2019, author = {Makrushin, Andrey and Neubert, Tom and Dittmann, Jana}, title = {Humans Vs. Algorithms: Assessment of Security Risks Posed by Facial Morphing to Identity Verification at Border Control}, series = {Konferenz: 14th International Conference on Computer Vision Theory and Applications, Prague, Czech Republic, 2019/ Titel: Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications}, booktitle = {Konferenz: 14th International Conference on Computer Vision Theory and Applications, Prague, Czech Republic, 2019/ Titel: Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications}, publisher = {SCITEPRESS - Science and Technology Publications}, address = {Prague, Czech Republic}, isbn = {978-989-758-354-4}, doi = {10.5220/0007378905130520}, pages = {513 -- 520}, year = {2019}, language = {en} } @inproceedings{MakrushinScheidatVielhauer2015, author = {Makrushin, Andrey and Scheidat, Tobias and Vielhauer, Claus}, title = {Capturing latent fingerprints from metallic painted surfaces using UV-VIS spectroscope}, series = {Konferenz: IS\&T/SPIE Electronic Imaging, 2015/ Titel: Proceedings of SPIE - The International Society for Optical Engineering}, booktitle = {Konferenz: IS\&T/SPIE Electronic Imaging, 2015/ Titel: Proceedings of SPIE - The International Society for Optical Engineering}, editor = {Alattar, Adnan M. and Memon, Nasir D. and Heitzenrater, Chad D.}, publisher = {SPIE. Digital Library}, address = {San Francisco, California, United States}, doi = {10.1117/12.2078876}, year = {2015}, language = {en} }