Exploring Usability and Legal Practice: Insights from German Judicial Users of Digital Forensics
Tobias Hoppmann, Leona Lassak, M. Angela Sasse, Zinaida Benenson
Abstract
Digital forensics has become an integral part of modern criminal proceedings, yet its effective integration remains challenging because of increasing data volumes, evolving technologies, and complex interactions between technical and legal stakeholders. Although prior work has focused primarily on digital forensic tools and methods, its broader procedural and organizational context has received limited attention. Building on emerging perspectives inspired by usability research and human-centered security, we conceptualize digital forensics as part of a socio-technical system within criminal proceedings. We consequently investigate this perspective through a survey of 101 practitioners from the judiciary of the German federal state of North Rhine-Westphalia, including public prosecutors, judges, and digital forensic experts. The results indicate a strong demand for improved integration of digital forensics into workflows, enhanced cross-domain communication, and a closer alignment of stakeholder expectations. They also uncover great potential for the improvement of digital forensics usability, e.g., through stronger interdisciplinary cooperation, easier and faster access to evidential data and results, or improvement of stakeholder training and education.
Create a lesson
Related papers
Analog Pin Directionality as an Exfiltration Attack Surface in Mixed-Signal ICs
Ramana Ranganatham, Chirag Adiga, Michael Zuzak et al.
Characterizing Network Centralization and Observability in the Remote MCP Ecosystem
Muhammad Abdullah Sohail
When Agents Look Like Beacons: NIDS Evasion by Model Context Protocol Traffic
Muhammad Abdullah Sohail
Hamming Ideals and Grobner Bases for ISD-like Syndrome Decoding
Roberto La Scala, Marco Marchesin, Sharwan K. Tiwari
ASLEval: Measuring Privacy Exposure Displacement in LLM Agent Sessions
Guosen Wu, Huizhen Huang, Guoxiong Long et al.
CASHEWS: Source Preprocessor for LLM-based Malicious Package Detection
Jean-Charles Noirot Ferrand, David Adei, Anders Møller et al.