# Investigating Wearable Fitness Applications: Data Privacy and Digital Forensics Analysis on Android
## 2 Review of the Literature  
This section provides a review of the most relevant literature on the current study. It also discusses their shortcomings and mentions how the current study improves on those shortcomings with our work. Previous research has primarily focused on analyzing Fitbit smartwatches and the Fitbit application on various Operating Systems, including Android, iOS, and Windows. Table 1 provides a summary review of the literature and the contributions of the current study. [PERSON] et al. [16] conducted a forensic analysis of the Fitbit Versa smartwatch on Android 9 and iOS 12. The authors provided a clear description of the relevant artifacts recovered from these two devices after using multiple extraction methods. The authors also provided a comprehensive comparison of the forensic acquisition capabilities of Cellebrite UFED and MSAB XRY. Similarly, [PERSON] and [PERSON] [12] conducted a forensic analysis of the Fitbit app when using a Fitbit Versa 2 smartwatch. The authors identified the privacy concerns resulting from any forensically relevant artifacts recovered from the Fitbit app on an Android 7 smartphone device. Furthermore, the authors tested all the free features offered by the Fitbit app and the Versa 2 smartwatch, where they performed various activities with the Versa 2 smartwatch, which generated data to be recovered. For example, the authors used Alexa voice commands, tracked a workout, linked a credit card to the smartwatch, generated notifications that appeared on the Versa 2 watch screen, and set alarms. They found that GPS locations, linked credit card information, health-related data such as heart rate and exercise activity data, and the user's latest GPS location were recoverable from the Fitbit app. In addition, the authors noted that artifacts related to app notifications are shown on the Fitbit smartwatch, and artifacts related to any interaction with Alexa on the Versa 2 were not recovered from the Fitbit app. The methodology followed [12] is used as the basis for our current study despite the fact that the authors used an older mobile operating system (Android 7) in their work. Our research improves on this shortcoming by focusing on investigating our chosen apps on one of the newest mobile operating systems widely used today, Android 10. [PERSON] et al. [13] conducted a forensic analysis of three fitness wearable devices: a Garmin Forerunner 110, a Fitbit Charge HR, and a generic low-cost HETP fitness tracker. The authors identified forensically relevant artifacts stored by these devices by manually examining their associated Windows 10 app (Fitbit) or directly connecting the wearable to a Windows 10 computer (Garmin). The HETP band only interacts with a mobile app. However, the authors were unable to view any data that may have been stored within the app. The authors found that the Garmin device and the Fitbit Windows 10 app record a wealth of forensically relevant data. Notably, they were able to recover details about the test runs they did to populate the devices with data, including GPS locations (Fitbit), deleted records (Garmin), group chat/post interactions (Fitbit), and other user and device information (both). However, these authors did not investigate what forensically relevant data can be recovered from the mobile apps of these devices, a limitation in our opinion. As such, our investigation will extend their work by conducting a forensic analysis of the Garmin Connect app on Android 10, while [PERSON] and [PERSON]'s work [12] filled the gap by investigating the Fitbit app on a mobile device. [PERSON] et al. [15] conducted a forensic analysis of the Mi Fit and Fitbit apps on an Android 7 device after using the Mi Band 2 and Fitbit Alta HR fitness trackers, respectively.