Webinar: Tutorial on Likelihood Ratios with Applications in Digital Forensics
Thursday, September 15 at 11:00 am - 12:00 pm CDTFree
CSAFE invites researchers, collaborators, and members of the broader forensics and statistics communities to participate in our Summer 2022 Webinar Series on Thursday, September 15, 2022, from 11:00am-Noon CT. The presentation will be “Tutorial on Likelihood Ratios with Applications in Digital Forensics.”
PhD Student – University of California, Irvine
Associate Director – Center for Machine Learning and Intelligent Systems, University of California, Irvine
To date, digital forensics research has largely focused on extracting and reconstructing information from devices and the cloud. In comparison, there has been relatively little work on statistical methodologies that can be used to analyze such data after this step. In this webinar, we will discuss statistical analyses in digital forensics, with a particular focus on likelihood ratios and ideas from Bayesian statistics. There will be three parts to the webinar.
First, we will begin with a general introduction to the concept of likelihood ratios. We will show how they can be constructed mathematically, how they can be interpreted, and how they have been broadly applied in forensics. We will discuss how strategies from Bayesian statistics can be incorporated into the statistical models used to construct the likelihood ratio and walk through simple motivating examples step-by-step.
Second, we will discuss the development of likelihood ratios in the context of digital forensics. We will consider the types of evidence available in digital forensics, the types of questions investigators may ask about this data, and how likelihood ratios can be used to address these questions. Building upon the first part of the webinar, we will present a likelihood ratio-based method for analyzing digital evidence data which uses a Bayesian approach.
Lastly, we will present results from applying these methods to real-world datasets related to digital evidence. We will discuss these results, limitations of the method, and how future research can improve upon this approach.
The webinars are free and open to the public, but researchers, collaborators and members of the broader forensics and statistics communities are encouraged to attend. Each 60-minute webinar will allow for discussion and questions.
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