Abstract : This paper presents methods for analyzing the topology of a Bayesian belief network created to qualify and quantify the strengths of investigative hypotheses and their supporting digital evidence. The methods, which enable investigators to systematically establish, demonstrate and challenge a Bayesian belief network, help provide a powerful framework for reasoning about digital evidence. The methods are applied to review a Bayesian belief network constructed for a criminal case involving BitTorrent file sharing, and explain the causal effects underlying the legal arguments.
Gilbert Peterson; Sujeet Shenoi. 8th International Conference on Digital Forensics (DF), Jan 2012, Pretoria, South Africa. Springer, IFIP Advances in Information and Communication Technology, AICT-383, pp.99-113, 2012, Advances in Digital Forensics VIII. 〈10.1007/978-3-642-33962-2_7〉
https://hal.inria.fr/hal-01523702
Contributeur : Hal Ifip
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Soumis le : mardi 16 mai 2017 - 17:10:11
Dernière modification le : vendredi 1 décembre 2017 - 01:17:04
Document(s) archivé(s) le : vendredi 18 août 2017 - 00:44:59
Hayson Tse, Kam-Pui Chow, Michael Kwan. Reasoning about Evidence using Bayesian Networks. Gilbert Peterson; Sujeet Shenoi. 8th International Conference on Digital Forensics (DF), Jan 2012, Pretoria, South Africa. Springer, IFIP Advances in Information and Communication Technology, AICT-383, pp.99-113, 2012, Advances in Digital Forensics VIII. 〈10.1007/978-3-642-33962-2_7〉. 〈hal-01523702〉
