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Mac Dermott, AM, Lea, S, Iqbal, F, Idowu, IO and Shah, B (2019) Forensic Analysis of Wearable Devices: Fitbit, Garmin and HETP watches. In: 2019 10th IFIP International Conference on New Technologies, Mobility and Security (NTMS) . (10 th IFIP International Conference on New Technologies, Mobility and Security, 24 June 2019 - 26 June 2019, Canary Islands, Spain).
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Forensic Analysis of Wearable Technology Final.pdf - Accepted Version Download (906kB) | Preview |
Abstract
Wearable technology has been on an exponential rise and shows no signs of slowing down. One category of wearable technology is Fitness bands, which have the potential to show a user’s activity levels and location data. Such information stored in fitness bands is just the beginning of a long trail of evidence fitness bands can store, which represents a huge opportunity to digital forensic practitioners. On the surface of recent work and research in this area, there does not appear to be any similar work that has already taken place on fitness bands and particularly, the devices in this study, a Garmin Forerunner 110, a Fitbit Charge HR and a Generic low-cost HETP fitness tracker. In this paper, we present our analysis of these devices for any possible digital evidence in a forensically sound manner, identifying files of interest and location data on the device. Data accuracy and validity of the evidence is shown, as a test run scenario wearing all of the devices allowed for data comparison analysis.
| Item Type: | Conference or Workshop Item (Paper) |
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| Additional Information: | © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Computer Science & Mathematics |
| Publisher: | IEEE |
| Date Deposited: | 03 Jun 2019 09:22 |
| Last Modified: | 12 Jun 2024 12:18 |
| DOI or ID number: | 10.1109/NTMS.2019.8763834 |
| URI: | https://researchonline.ljmu.ac.uk/id/eprint/10771 |
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