Abstract
Evidence analysis is one of the Digital Forensics tasks and involves examining fragmented incomplete knowledge and reasoning on it, in order to reconstruct plausible crime scenarios. After more than one year of activity within the DigForASP COST Action, the lack of real data about movements of people in crime scenes emerged as a major limitation to the need of testing the DigForASP prototypes that exploit Artificial Intelligence and Automated Reasoning for evidence analysis.
In this paper we present DigForSim, an Agent Based Modeling and Simulation tool aimed at producing synthetic, controllable data on the movements of agents in the crime scene, in form of files logging the agents’ position at given time points. These log files serve as benchmarks for the DigForASP reasoning prototypes.
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Notes
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CA17124, https://digforasp.uca.es, funded for four years starting from 09/2018 by the European Cooperation in Science and Technology (COST, www.cost.eu).
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https://github.com/VivianaMascardi/DigForSim and https://github.com/VivianaMascardi/DigForReason, respectively; Alessandro Biagetti’s Master Thesis (with many experiments, figures and screenshots that could not be inserted in this paper for space constraints) and a link to a video showing DigForSim at work are also available in the DigForSim repository.
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Acknowledgements
This paper is based upon work from COST Action DigForASP, supported by COST (European Cooperation in Science and Technology). We acknowledge all the DigForASP partners for the exciting and constructive discussions.
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Biagetti, A., Ferrando, A., Mascardi, V. (2020). The DigForSim Agent Based Simulator of People Movements in Crime Scenes. In: Demazeau, Y., Holvoet, T., Corchado, J., Costantini, S. (eds) Advances in Practical Applications of Agents, Multi-Agent Systems, and Trustworthiness. The PAAMS Collection. PAAMS 2020. Lecture Notes in Computer Science(), vol 12092. Springer, Cham. https://doi.org/10.1007/978-3-030-49778-1_4
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