activity
20242026
most citedEnvId: A Metric Learning Approach for Forensic Few-Shot Identification of Unseen Environments

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CR2026

Beyond Predictable Paths: Redefining AI Security Incident Reporting for Agents

Anastasia Pustozerova, Eugene Bagdasarian, Luca Beurer-Kellner +22

AI agents are being deployed rapidly, accompanied by a growing number of AI-specific attacks and corresponding incidents. As incident reporting becomes increasingly important for l…

cs.LG2025

Sure! Here's a short and concise title for your paper: "Contamination in Generated Text Detection Benchmarks"

Philipp Dingfelder, Christian Riess

Large language models are increasingly used for many applications. To prevent illicit use, it is desirable to be able to detect AI-generated text. Training and evaluation of such d…

cs.CV2025

Three Forensic Cues for JPEG AI Images

Sandra Bergmann, Fabian Brand, Christian Riess

The JPEG standard was vastly successful. Currently, the first AI-based compression method ``JPEG AI'' will be standardized. JPEG AI brings remarkable benefits. JPEG AI images exhib…

cs.CV2024

Trustworthy Compression? Impact of AI-based Codecs on Biometrics for Law Enforcement

Sandra Bergmann, Denise Moussa, Christian Riess

Image-based biometrics can aid law enforcement in various aspects, for example in iris, fingerprint and soft-biometric recognition. A critical precondition for recognition is the a…

cs.SD2024★ 1 cited

EnvId: A Metric Learning Approach for Forensic Few-Shot Identification of Unseen Environments

Denise Moussa, Germans Hirsch, Christian Riess

Audio recordings may provide important evidence in criminal investigations. One such case is the forensic association of a recorded audio to its recording location. For example, a…