Reasoning About Evidence Using Bayesian Networks

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.

[1]  Keith Marzullo,et al.  Principles-driven forensic analysis , 2005, NSPW '05.

[2]  Phillip I. Good,et al.  Applying Statistics in the Courtroom , 2002 .

[3]  Indrajit Ray,et al.  Advances in Digital Forensics IV , 2008 .

[4]  David Poole,et al.  Probabilistic Horn Abduction and Bayesian Networks , 1993, Artif. Intell..

[5]  Venansius Baryamureeba,et al.  The Enhanced Digital Investigation Process Model , 2004 .

[6]  Franco Taroni,et al.  Statistics and the Evaluation of Evidence for Forensic Scientists , 2004 .

[7]  Claude Roux,et al.  Statistics and the Evaluation of Evidence for Forensic Scientists, by Colin G. G. Aitken and Franco Taroni 2nd edition. John Wiley and Sons, 2004. , 2006 .

[8]  Sheau-Dong Lang,et al.  From digital forensic report to Bayesian network representation , 2009, 2009 IEEE International Conference on Intelligence and Security Informatics.

[9]  Seamus O. Ciardhuáin,et al.  An Extended Model of Cybercrime Investigations , 2004, Int. J. Digit. EVid..

[10]  J A Lambert,et al.  A model for case assessment and interpretation. , 1998, Science & justice : journal of the Forensic Science Society.

[11]  Robert Cowell,et al.  Introduction to Inference for Bayesian Networks , 1998, Learning in Graphical Models.

[12]  Hendrik Prakken.  Proceedings of the Eighteenth International Conference on Artificial Intelligence and Law , 2021 .

[13]  Kevin B. Korb,et al.  Bayesian Artificial Intelligence , 2004, Computer science and data analysis series.

[14]  Nianjun Liu,et al.  An Embedded Bayesian Network Hidden Markov Model for Digital Forensics , 2006, ISI.

[15]  C. M. Breur.  New trends in criminal investigation and evidence , 2000 .

[16]  Judea Pearl,et al.  Probabilistic reasoning in intelligent systems , 1988 .

[17]  Jeroen Keppens,et al.  Probabilistic abductive computation of evidence collection strategies in crime investigation , 2005, ICAIL '05.

[18]  A. Dawid,et al.  Probabilistic expert systems for DNA mixture profiling. , 2003, Theoretical population biology.

[19]  Henry Prakken,et al.  Argumentation schemes and generalisations in reasoning about evidence , 2003, ICAIL.

[20]  Yang Xiang,et al.  Bayesian probabilistic reasoning in design , 1993, Proceedings of IEEE Pacific Rim Conference on Communications Computers and Signal Processing.

[21]  Judea Pearl,et al.  Probabilistic reasoning in intelligent systems - networks of plausible inference , 1991, Morgan Kaufmann series in representation and reasoning.

[22]  Ronald Prescott Loui,et al.  Progress on Room 5: a testbed for public interactive semi-formal legal argumentation , 1997, ICAIL '97.

[23]  Timothy Grance,et al.  Guide to Integrating Forensic Techniques into Incident Response , 2006 .

[24]  P. Good.  Applying Statistics in the Courtroom: A New Approach for Attorneys and Expert Witnesses , 2001 .

[25]  C. Aitken,et al.  Statistics and the Evaluation of Evidence for Forensic Scientists: Aitken/Statistics and the Evaluation of Evidence for Forensic Scientists , 2005 .

[26]  David J. Spiegelhalter,et al.  Local computations with probabilities on graphical structures and their application to expert systems , 1990 .

[27]  Jeroen Keppens,et al.  A model based reasoning approach for generating plausible crime scenarios from evidence , 2003, ICAIL.

[28]  Fred Cohen.  Two Models of Digital Forensic Examination , 2009, 2009 Fourth International IEEE Workshop on Systematic Approaches to Digital Forensic Engineering.

[29]  D. Walton,et al.  Argumentation and Theory of Evidence , 2000 .