| Title | Forensic Analysis of Fitbit Versa: Android vs iOS |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | Williams, Joseph, MacDermott, Áine, Stamp, Kellyann, Iqbal, Farkhund |
| Conference Name | 2021 IEEE Security and Privacy Workshops (SPW) |
| Keywords | Cellebrite, cloud forensics, compositionality, Conferences, data mining, Databases, digital forensics, fitbit, Fitbit forensics, forensic analysis, human factors, ios, iOS Security, Metrics, privacy, pubcrawl, resilience, Resiliency, security, wearable computers |
| Abstract | Fitbit Versa is the most popular of its predecessors and successors in the Fitbit faction. Increasingly data stored on these smart fitness devices, their linked applications and cloud datacenters are being used for criminal convictions. There is limited research for investigators on wearable devices and specifically exploring evidence identification and methods of extraction. In this paper we present our analysis of Fitbit Versa using Cellebrite UFED and MSAB XRY. We present a clear scope for investigation and data significance based on the findings from our experiments. The data recovery will include logical and physical extractions using devices running Android 9 and iOS 12, comparing between Cellebrite and XRY capabilities. This paper discusses databases and datatypes that can be recovered using different extraction and analysis techniques, providing a robust outlook of data availability. We also discuss the accuracy of recorded data compared to planned test instances, verifying the accuracy of individual data types. The verifiable accuracy of some datatypes could prove useful if such data was required during the evidentiary processes of a forensic investigation. |
| DOI | 10.1109/SPW53761.2021.00052 |
| Citation Key | williams_forensic_2021 |
Forensic Analysis of Fitbit Versa: Android vs iOS