A fitness tracker monitors our daily activity by measuring distance walked (or run), calorie consumption, heartbeat and quality of sleep. Although originally designed to check the user’s health, its data is important in verifying the veracity of interrogation responses of the suspect, or the activities of the victim near the time of the incident. Xiaomi Mi Band 2 and Fitbit Alta HR are representative fitness trackers which allow users to view measured data on connected mobile devices. We compare the functionality of the two wearable devices, select the data that must be acquired (based on the Android device used), and provide the analysis methods for each file from the perspective of digital forensics.
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A measure of the delight or annoyance of a customer’s experiences with a service.
The process of collecting and analyzing data to submit electronic evidence to law enforcement.
A set of software development tools that allows the creation of applications.
Mobile data acquisition tool developed by Hancom GMD.
Google-provided services that covers local information around the world, including satellite imagery, maps, terrain and ED building information.
If it is a normal record, ‘synced’ should be recorded.
This scenario was adapted from that given in the DFRWS IoT Forensic Challenge (2017-2018).
Korea Standard Time (KST)
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This work was supported by Institute for Information & communications Technology Promotion (IITP) grant funded by the Korea government (MSIT) (No.2017-0-00344, Deciphering and forensic analysis of recent mobile devices).
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This article is part of the Topical Collection: Special Issue on IoT System Technologies based on Quality of Experience
Guest Editors: Cho Jaeik, Naveen Chilamkurti, and SJ Wang
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Kang, S., Kim, S. & Kim, J. Forensic analysis for IoT fitness trackers and its application. Peer-to-Peer Netw. Appl. 13, 564–573 (2020). https://doi.org/10.1007/s12083-018-0708-3
- Fitness tracker
- Xiaomi Mi Band 2
- Fitbit Alta HR
- IoT forensic