Forensic camera device identification addresses the scenario, where an investigator has two pieces of evidence: a digital image from an unknown camera involved in a crime, such as child pornography, and a person of interest’s (POI’s) camera. The investigator wants to determine whether the image was taken by the POI’s camera. Small manufacturing imperfections in the photodiode cause slight variations among pixels in the camera sensor array. These spatial variations, called photo-response non-uniformity (PRNU), provide an identifying characteristic, or fingerprint, of the camera. Most work in camera device identification leverages the PRNU of the questioned image and the POI’s camera to make a yes-or-no decision. As in other areas of forensics, there is a need to introduce statistical and probabilistic methods that quantify the strength of evidence in favor of the decision. Score-based likelihood ratios (SLRs) have been proposed in the forensics community to do just that. Several types of SLRs have been studied individually for camera device identification. We introduce a framework for calculating and comparing the performance of three types of SLRs — source-anchored, trace-anchored, and general match. We employ PRNU estimates as camera fingerprints and use correlation distance as a similarity score. Three types of SLRs are calculated for 48 camera devices from four image databases: ALASKA; BOSSbase; Dresden; and StegoAppDB. Experiments show that the trace-anchored SLRs perform the best of these three SLR types on the dataset and the general match SLRs perform the worst.
Source-Anchored, Trace-Anchored, and General Match Score-Based Likelihood Ratios for Camera Device Identification

Journal: Journal of Forensic Sciences
Published: 2022
Primary Author: Stephanie Reinders
Secondary Authors: Yong Guan, Danica Ommen, Jennifer Newman
Type: Publication
Related Resources
Towards a likelihood ratio approach for bloodstain pattern analysis
In this work, we explore the application of likelihood ratio as a forensic evidence assessment tool to evaluate the causal mechanism of a bloodstain pattern. It is assumed that there…
An Open-Source Implementation of the CMPS Algorithm for Assessing Similarity of Bullets
In this paper, we introduce the R package cmpsR, an open-source implementation of the Congruent Matching Profile Segments (CMPS) method developed at the National Institute of Standards and Technology (NIST)…
LibDroid: Summarizing information flow of Android Native Libraries via Static Analysis
With advancements in technology, people are taking advantage of mobile devices to access e-mails, search the web, and video chat. Therefore, extracting evidence from mobile phones is an important component…
Evaluating Reference Sets for Score-Based Likelihood Ratios for Camera Device Identification
An investigator wants to know if an illicit image captured by an unknown camera was taken by a person of interest’s (POI’s) phone. Score-based likelihood ratios (SLRs) have been used…