Benedikt Lorch › IT Security Infrastructures Lab

Benedikt Lorch, M. Sc.

Organization: Department of Computer Science
Working group: Chair of Computer Science 1 (IT Security Infrastructures)
Phone number: +49 9131 85 69918
Fax number: +49 9131 85 69919
Email: benedikt.lorch@fau.de
Website: https://www.cs1.tf.fau.de/person/benedikt-lorch/
Address:
Martensstr. 3
91058 Erlangen
Room 12.139

PhD candidate in the multimedia security group and member of the research training group Cybercrime and Forensic Computing. My research interests include image forensics, computer vision, and machine learning.

Recent projects

Image forensics from chroma wrinkles

Image splicing localization where both host and donor contain the artifact, however, the artifacts in the inserted region are desynchronized with the host.

This work presents a novel artifact that can be used to fingerprint the JPEG compression library. The artifact arises from chroma subsampling in one of the most popular JPEG implementations. Due to integer rounding, every second column of the compressed chroma channel appears on average slightly brighter than its neighboring columns, which is why we call the artifact a chroma wrinkle. We theoretically derive the chroma wrinkle footprint in DCT domain, and use this footprint for detecting chroma wrinkles.
Paper | Slides

Forensic reconstruction of severely degraded license plates

Low-quality image of South Carolina license plate on car rear. The low resolution and the presence of additive noies make it nearly impossible to decipher the license number.

Forensic investigations often have to contend with extremely low-quality images that can provide critical evidence. Recent work has shown that, although not visually apparent, information can be recovered from such low-resolution and degraded images. We developed a CNN-based approach to decipher the contents of low-quality images of license plates.
Paper | Slides | GitHub

Quick links

Forensics conference deadlines

PGP

Key ID	D7994F61EECD8C75
SHA-1 Fingerprint	1781 F23E FB55 50E6 BA75 ED4E D799 4F61 EECD 8C75
Public Key	ASCII-armored

Publications

2019

Lorch, B., Agarwal, S., & Farid, H. (2019). Forensic Reconstruction of Severely Degraded License Plates. In Society for Imaging Science & Technology (Eds.), Electronic Imaging. Burlingame, CA, US.
URL: https://faui1-files.cs.fau.de/public/mmsec/license-plates/ei2019_forensic_reconstruction_of_severely_degraded_license_plates.pdf
Lorch, B., & Riess, C. (2019). Image Forensics from Chroma Subsampling of High-Quality JPEG Images. In Proceedings of the ACM Workshop on Information Hiding and Multimedia Security. Paris, FR.
URL: https://faui1-files.cs.fau.de/public/publications/mmsec/2019-Lorch-IFC.pdf

2017

Lorch, B., Vaillant, G., Baumgartner, C., Bai, W., Rueckert, D., & Maier, A. (2017). Automated Detection of Motion Artefacts in MR Imaging Using Decision Forests. Journal of Medical Engineering, 2017. https://dx.doi.org/10.1155/2017/4501647

2015

Lorch, B., Berger, M., Hornegger, J., & Maier, A. (2015). Projection and Reconstruction-Based Noise Filtering Methods in Cone Beam CT. In Bildverarbeitung für die Medizin 2015 (pp. 59-64). Lübeck.
URL: https://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2015/Lorch15-PAR.pdf
Mullan, P., Kanzler, C., Lorch, B., Schroeder, L., Winkler, L., Larissa, L.,... Pasluosta, C.F. (2015). Unobtrusive Heart Rate Estimation during Physical Exercise using Photoplethysmographic and Acceleration Data. In 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society EMBC ’15. Milano.