Abstract
Forensic-ready software systems integrate preparedness for digital forensic investigation into their design. It includes ensuring the production of potential evidence with sufficient coverage and quality to improve the odds of successful investigation or admissibility. However, the design of such software systems is challenging without in-depth forensic readiness expertise. Thus, this paper presents a tool suite to help the designer. It includes a graphical editor for creating system models in BPMN4FRSS notation, an extended BPMN with forensic readiness constructs, and an analyser utilising Z3 solver for satisfiability checking of formulas derived from the models. It verifies the models’ validity, provides targeted hints to enhance forensic readiness capabilities, and allows for what-if analysis of potential evidence quality.
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Notes
- 1.
Note the difference: potential digital evidence – potentially useable for future investigation, and digital evidence – used to satisfy or refute the investigation hypothesis.
- 2.
The documentation is available at: https://freas-tools.github.io/wiki/.
- 3.
Code, models, and a video demo are available at: https://doi.org/10.58126/bcxs-cr23.
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Acknowledgement
The work was supported by the Grant Agency of Masaryk University (GAMU) project “Forensic Support for Building Trust in Smart Software Ecosystems”, registration number MUNI/G/1142/2022. It was also co-founded by the European Union under Grant Agreement No. 101087529. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or European Research Executive Agency. Neither the European Union nor the granting authority can be held responsible for them.
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Daubner, L., Maksović, S., Matulevičius, R., Buhnova, B., Sedlác̆ek, T. (2024). Forensic-Ready Analysis Suite: A Tool Support for Forensic-Ready Software Systems Design. In: Araújo, J., de la Vara, J.L., Santos, M.Y., Assar, S. (eds) Research Challenges in Information Science. RCIS 2024. Lecture Notes in Business Information Processing, vol 514. Springer, Cham. https://doi.org/10.1007/978-3-031-59468-7_6
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