This research project focused on interpreting Integrated Ballistics Identification System (IBIS) data combined with Bayesian networking to provide a statistical analysis of firearm/cartridge identification.
The study indicated that a better understanding is required for the causes of the relatively high variability in cartridges cases fired by the same firearm as measured by Integrated Ballistics Identification System (IBIS) scores. An initial attempt to answer this question was done by simulating the minimum number of cartridge cases required to produce a distribution equivalent to that of the firearm. In the study, the breech face (BF) and firing pin (FP) scores generated by the IBIS were used to assess the ability of the system to classify an "unknown" cartridge case into a same-gun or different-gun category. The IBIS system does not provide for an easy means to use the combination of the BF and FP scores. The reliability of the IBIS system was assessed using the NIST Standard Reference Material 2461 (standard cartridge case). A 2D IBIS heritage system was compared to the new 3D IBIS system and found that the results were very well correlated. Twenty sets of known and questioned cartridge cases, from a large collection which had been analyzed by operational firearms examiners, were examined and tested using the Bayesian networks. Out of the 20 comparisons, there were eight true positives, seven true negatives, five false negatives, and zero false positives. In all instances of eliminations, the support for the different-gun hypothesis was, at minimum, strong. Overall, this study supports the interpretation of IBIS results through Bayesian networks. Improvements to the manner in which results are made available to the user will allow for more in-depth analysis of such results.