TY - CHAP A1 - Kraetzer, Christian A1 - Makrushin, Andrey A1 - Neubert, Tom A1 - Hildebrandt, Mario A1 - Dittmann, Jana T1 - Modeling Attacks on Photo-ID Documents and Applying Media Forensics for the Detection of Facial Morphing T2 - 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 Y1 - 2017 UR - https://dl.acm.org/doi/10.1145/3082031.3083244 SN - 978-1-4503-5061-7 U6 - https://doi.org/10.1145/3082031.3083244 SP - 21 EP - 32 PB - ACM CY - Philadelphia Pennsylvania USA ER - TY - CHAP A1 - Hildebrandt, Mario A1 - Neubert, Tom A1 - Makrushin, Andrey A1 - Dittmann, Jana T1 - Benchmarking face morphing forgery detection: Application of stirtrace for impact simulation of different processing steps T2 - Konferenz: 2017 5th International Workshop on Biometrics and Forensics (IWBF), 2017/ Titel: 2017 5th International Workshop on Biometrics and Forensics (IWBF) N2 - 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. Y1 - 2017 UR - http://ieeexplore.ieee.org/document/7935087/ SN - 978-1-5090-5791-7 U6 - https://doi.org/10.1109/IWBF.2017.7935087 SP - 1 EP - 6 PB - IEEE CY - Coventry, United Kingdom ER - TY - CHAP A1 - Neubert, Tom ED - Kraetzer, Christian ED - Shi, Yun-Qing ED - Dittmann, Jana ED - Kim, Hyoung Joong T1 - Face Morphing Detection: An Approach Based on Image Degradation Analysis T2 - Konferenz: International Workshop on Digital Watermarking, 2017/ Titel: Digital Forensics and Watermarking N2 - In 2014 a novel identity theft scheme targeting specific application scenarios in face biometrics was introduced. In this scheme, a so called face morph melts two or more face images of different persons into one image, which is visually similar to multiple real world persons. Based on this non authentic image, it is possible to apply for an image based identity document to be issued by a corresponding authority. Thus, multiple persons can use such a document to pass image based person verification scenarios with a single document containing an artificially weakened template. Currently there is no reliable existing security mechanism to detect this attack. T3 - Lecture notes in computer science - 10431 Y1 - 2017 UR - http://link.springer.com/10.1007/978-3-319-64185-0_8 SN - 978-3-319-64184-3 978-3-319-64185-0 U6 - https://doi.org/10.1007/978-3-319-64185-0_8 SP - 93 EP - 106 PB - Springer International Publishing CY - Magdeburg, Germany ER - TY - CHAP A1 - Makrushin, Andrey A1 - Neubert, Tom A1 - Dittmann, Jana T1 - Automatic Generation and Detection of Visually Faultless Facial Morphs T2 - 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 N2 - 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. Y1 - 2017 UR - http://www.scitepress.org/DigitalLibrary/Link.aspx?doi=10.5220/0006131100390050 SN - 978-989-758-225-7 978-989-758-226-4 978-989-758-227-1 U6 - https://doi.org/10.5220/0006131100390050 SP - 39 EP - 50 PB - SCITEPRESS - Science and Technology Publications CY - Porto, Portugal ER -