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.
https://hal.inria.fr/hal-01523702 Contributor : Hal IfipConnect in order to contact the contributor Submitted on : Tuesday, May 16, 2017 - 5:10:11 PM Last modification on : Thursday, March 5, 2020 - 4:46:27 PM Long-term archiving on: : Friday, August 18, 2017 - 12:44:59 AM
Hayson Tse, Kam-Pui Chow, Michael Kwan. Reasoning about Evidence using Bayesian Networks. 8th International Conference on Digital Forensics (DF), Jan 2012, Pretoria, South Africa. pp.99-113, ⟨10.1007/978-3-642-33962-2_7⟩. ⟨hal-01523702⟩