Document Type
Presentation
Conference
DFRWS 2020
Publication Version
Published Version
Publication Date
6-2020
Conference Date
June 3-5, 2020
Abstract
A common question in forensic analysis is whether two observed data sets originated from the same source or from different sources. Statistical approaches to addressing this question have been widely adopted within the forensics community, particularly for DNA evidence. Here we investigate the application of statistical approaches to same-source forensic questions for spatial event data, such as determining the likelihood that two sets of observed GPS locations were generated by the same individual. We develop two approaches to quantify the strength of evidence in this setting. The first is a likelihood ratio approach based on modeling the spatial event data directly. The second approach is to instead measure the similarity of the two observed data sets via a score function and then assess the strength of the observed score resulting in the score-based likelihood ratio. A comparative evaluation using geolocated Twitter event data from two large metropolitan areas shows the potential efficacy of such techniques.
Copyright Owner
The Authors
Copyright Date
2020
Language
en
File Format
application/pdf
Recommended Citation
Galbraith, Christopher; Smyth, Padhraic; and Stern, Hal S., "Statistical Methods for the Forensic Analysis of Geolocated Event Data" (2020). CSAFE Presentations and Proceedings. 67.
https://lib.dr.iastate.edu/csafe_conf/67
Comments
This is a presented paper published as Galbraith, Christopher, Padhraic Smyth, and Hal S. Stern. "Statistical methods for the forensic analysis of geolocated event data." Digital Investigation (2020).