Reasoning about Evidence using Bayesian Networks
Overview & Synopsis
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.
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hal.science)
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Document Information
| Document Title | Reasoning about Evidence using Bayesian Networks |
|---|---|
| Author / Organization | Hayson Tse, Kam-Pui Chow, Michael Kwan |
| Subject & Discipline | Multidisciplinary Academic Open Research |
| Categories | Science & Mathematics |
| Publication Year | 2012 |
| License / Rights | Open Access / Creative Commons |
| Resource Verification | Listed PDF (Verification Pending) |
| Original Host Website |
HAL Open Science
(hal.science)
|
| File Format | application/pdf (Portable Document Format) |
| Language | EN |
| Catalog ID | DOC-239842 |
| Original Source Link | Visit Source Page on hal.science » |