Benedikt Lorch, MSc
Research Assistant

E-mailbenedikt.lorch@uibk.ac.at
Phone+43 512 507-53489
AddressTechnikerstraße 21A, 6020 Innsbruck, Austria
OfficeICT 3N01
Benedikt Lorch, MSc

Research Interests

  • Steganography and steganalysis
  • Multimedia forensics
  • Machine learning

Positions

since 10/2022 Research assistant, Security and Privacy Lab, University of Innsbruck, Austria
09/2018 – 09/2022 Research assistant, IT Security Infrastructures Lab, Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany
04/2014 – 08/2015 Student assistant, Pattern Recognition Lab, Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany

Education

2015 – 2018 M.Sc. in Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany
11/2017 – 05/2018 Visiting student researcher, Visual Computing Lab, Dartmouth College, USA
2012 – 2016 B.Sc. in Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany
10/2015 – 02/2016 Visiting student researcher, Biomedical Image Analysis Group, Imperial College London, UK

Publications

  • Lorch, B., Scheler, N., and Riess, C. Compliance Challenges in Forensic Image Analysis Under the Artificial Intelligence Act. In European Signal Processing Conference. 2022.
  • Schneider, J., Düsel, L., Lorch, B., Drafz, J., and Freiling, F. Prudent Design Principles for Digital Tampering Experiments. Forensic Science International: Digital Investigation, 40, (April 2022).
  • Lorch, B., Franziska, Schirrmacher, Maier, A., and Riess, C. Reliable Camera Model Identification Using Sparse Gaussian Processes. IEEE Signal Processing Letters, 28, (March 2021), 912–916.
  • Kaiser, P., Schirrmacher, F., Lorch, B., and Riess, C. Learning to Decipher License Plates in Severely Degraded Images. In International Conference on Pattern Recognition Workshops. Springer, 2021, pp. 544–559.
  • Pan, J., Maier, A., Lorch, B., and Riess, C. Reliable Camera Model Identification Through Uncertainty Estimation. In IEEE International Workshop on Biometrics and Forensics. 2021.
  • Lorch, B., Maier, A., and Riess, C. Reliable JPEG Forensics via Model Uncertainty. In IEEE International Workshop on Information Forensics and Security. 2020.
  • Maier, A., Lorch, B., and Riess, C. Toward Reliable Models for Authenticating Multimedia Content: Detecting Resampling Artifacts With Bayesian Neural Networks. In IEEE International Conference on Image Processing. 2020, pp. 1251–1255.
  • Schirrmacher, F., Lorch, B., Stimpel, B., Köhler, T., and Riess, C. SR^2: Super-Resolution With Structure-Aware Reconstruction. In IEEE International Conference on Image Processing. 2020, pp. 533–537.
  • Lorch, B. and Riess, C. Image Forensics from Chroma Subsampling of High-Quality JPEG Images. In ACM Workshop on Information Hiding and Multimedia Security. New York, NY, USA, 2019, pp. 101–106.
  • Lorch, B., Agarwal, S., and Farid, H. Forensic Reconstruction of Severely Degraded License Plates. In Electronic Imaging. 2019.
  • Lorch, B., Vaillant, G., Baumgartner, C., Bai, W., Rueckert, D., and Maier, A. Automated Detection of Motion Artefacts in MR Imaging Using Decision Forests. Journal of Medical Engineering, (June 2017), 1–9.
  • Mullan, P., M. Kanzler, C., Lorch, B., et al. Unobtrusive Heart Rate Estimation During Physical Exercise Using Photoplethysmographic and Acceleration Data. In International Conference of the IEEE Engineering in Medicine and Biology Society. 2015, pp. 6114–6117.
  • Lorch, B., Berger, M., Hornegger, J., and Maier, A. Projection and Reconstruction-Based Noise Filtering Methods in Cone Beam CT. In Bildverarbeitung für die Medizin. Springer Berlin Heidelberg, 2015, pp. 59–64.

Awards

  • ASQF award for outstanding studies (February 2019)
  • DAAD scholarship for internship abroad (September 2017)

Projects