Skip to content

Statistical models to predict exposure settings using two different iPhone camera apps

Published: 2020
Primary Author: Kurt Michael Kabriel
Research Area: Digital

The StegoAppDB [Newman, J. (2019)] is a digital image database containing camera data from Android and iPhone mobile phones and developed for forensic purposes. Taken with a custom-designed camera app called Cameraw rather than the camera app native to the mobile device, it is not known what relation exists between the exposure settings of images taken with Cameraw and those with the native app. This knowledge would provide the digital image forensic analyst more information to answer this question: are the images in the database representative of images encountered in forensic settings? To this end, this thesis provides results from experiments designed to model the relation between exposure settings between images taken from the two camera apps.For purposes of this thesis, the term exposure settings denotes the exposure time and the ISO value excluding the lens aperture variable, as that last variable is fixed on a mobile phone.In this thesis, images acquired from four iOS devices – an iPhone 7, iPhone 8, and two iPhone Xs – are analyzed to develop regression models that fit exposure settings from image data for each device. Specific image acquisition experiments are designed to collect pairs of images very close in time and space from each of the two apps so that their exposure settings could be compared. A broad range of ISO and exposure time values are collected to represent a variety of exposure settings possible on a mobile device. Several different regression models with cross validation are developed for the data from each phone, and generalized linear models are also applied. Errors for the training, validation and testing sets are used to evaluate the performance of individual models, and the adjusted R-squared statistic is used to compare performances across models. The best models with respect to the performance measures are identified for each type of analysis and for each iPhone.The results show that most of the linear models typically model the data fairly well, and exposure settings can be predicted from the models. One notable exception is the iPhone 7: the best models for the iPhone 7 are different because the exposure setting data differs significantly from the other two iPhone models’ exposure setting data. The results in this thesis show that in a very limited case, for these four devices, the Cameraw app can be a reliable alternative to the native camera app.

Related Resources

Forensic Analysis of Android Cloud SDKs

Forensic Analysis of Android Cloud SDKs

This presentation is from the 76th Annual Conference of the American Academy of Forensic Sciences (AAFS), Denver, Colorado, February 19-24, 2024.
The Impact of Multi-Camera Smart Phones on Source Camera Identification

The Impact of Multi-Camera Smart Phones on Source Camera Identification

An investigator has a questioned image from an unknown source and wants to determine whether it came from a camera on a person of interest’s smartphone. This scenario is referred…
Likelihood ratios for changepoints in categorical event data with applications in digital forensics

Likelihood ratios for changepoints in categorical event data with applications in digital forensics

We investigate likelihood ratio models motivated by digital forensics problems involving time-stamped user-generated event data from a device or account. Of specific interest are scenarios where the data may have…
Producing Datasets: Capturing Images on Multi-Camera Smartphones for Source Camera Identification

Producing Datasets: Capturing Images on Multi-Camera Smartphones for Source Camera Identification

This poster introduces the new CSAFE Multi-camera Smartphone Image Database and describes how the image were collected and reviewed.