Watch What You Wear: Preliminary Forensic Analysis of Smart Watches

Baggili, Ibrahim; Oduro, Jeff; Anthony, Kyle; Breitinger, Frank; McGee, Glenn

doi:10.1109/ares.2015.39

Cited by 42 publications

(16 citation statements)

References 15 publications

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“…IoT forensics has been widely studied in recent literature [2,[10][11][12][13][14][15]. There has also been recent literature and studies that have focused on recovering forensic artifacts of interests from virtual assistant enabled devices and their companion devices.…”

Section: Related Workmentioning

confidence: 99%

Forensic Investigation of Google Assistant

Akinbi

Berry

2020

SN COMPUT. SCI.

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Google Nest devices have seen a rise in demand especially with Google’s huge advantage in search engine results and a complex ecosystem that consists of a range of companion devices and compatible mobile applications integrated and interacting with its virtual assistant, Google Assistant. This study undertakes the forensics extraction and analysis of client-centric and cloud-native data remnants left behind on Android smartphones by the Google Home and Google Assistant apps used to control a Google Nest device. We identified the main database and file system storage location central to the Google Assistant ecosystem. From our analysis, we show forensic artifacts of interest associated with user account information, the chronology and copies of past voice conversations exchanged, and record of deleted data. The findings from this study describe forensic artifacts that could assist forensic investigators and can facilitate a criminal investigation.

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Section: Related Workmentioning

confidence: 99%

Forensic Investigation of Google Assistant

Akinbi

Berry

2020

SN COMPUT. SCI.

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“…Smartwatches are small, expensive and popular. As a result, they have been deemed a feasible target for theft (Baggili et al, 2015). Through using a screen lock, personal data is better-protected.…”

Section: Protective Features and Concern Scenariosmentioning

confidence: 99%

Smartwatch games: Encouraging privacy-protective behaviour in a longitudinal study

Williams

Nurse

Creese

2019

Computers in Human Behavior

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While the public claim concern for their privacy, they frequently appear to overlook it. This disparity between concern and behaviour is known as the Privacy Paradox. Such issues are particularly prevalent on wearable devices. These products can store personal data, such as text messages and contact details. However, owners rarely use protective features. Educational games can be effective in encouraging changes in behaviour. Therefore, we developed the first privacy game for (Android) Wear OS watches. 10 participants used smartwatches for two months, allowing their high-level settings to be monitored. Five individuals were randomly assigned to our treatment group, and they played a dynamically-customised privacy-themed game. To minimise confounding variables, the other five received the same app but lacking the privacy topic. The treatment group improved their protection, with their usage of screen locks significantly increasing (p = 0.043). In contrast, 80% of the control group continued to never restrict their settings. After the posttest phase, we evaluated behavioural rationale through semistructured interviews. Privacy concerns became more nuanced in the treatment group, with opinions aligning with behaviour. Actions appeared influenced primarily by three factors: convenience, privacy salience and data sensitivity. This is the first smartwatch game to encourage privacy-protective behaviour.

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“…In respect to smart TVs, in [ 29 ] the Amazon Fire TV stick is studied and guidelines on how to acquire a forensic image of the device when performing a chip-off are given, and a list is given of the artifacts that can be found on it, although the analysis is not very extensive. Other relevant devices are smart watches, which contain a considerable amount of sensitive information, as is shown in [ 30 ], in which two models are examined and a forensic analysis is performed on them, explaining the acquisition process and the tools that are used. The information obtained from them is not very relevant for an investigation, but the process followed is very interesting and significant in helping explain how to manage this kind of device.…”

Section: Related Workmentioning

confidence: 99%

Non-Volatile Memory Forensic Analysis in Windows 10 IoT Core

Gómez¹,

Roldán-Gómez²,

Mondéjar³

et al. 2019

Entropy

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The increase in the number of cybersecurity incidents in which internet of things (IoT) devices are involved has called for an improvement in the field of computer forensics, which needs to provide techniques in order to perform complete and efficient investigations in this new environment. With the aim of doing so, new devices and systems are being studied in order to offer guidelines for investigators on how to examine them. This papers follows this approach and presents a forensic analysis of the non-volatile memory of Windows 10 IoT Core. It details how the investigation should be performed and highlights the relevant information that can be extracted from storage. In addition, a tool for the automation of the retrieval of the pieces of evidence detected is provided.

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Watch What You Wear: Preliminary Forensic Analysis of Smart Watches

Cited by 42 publications

References 15 publications

Forensic Investigation of Google Assistant

Forensic Investigation of Google Assistant

Smartwatch games: Encouraging privacy-protective behaviour in a longitudinal study

Non-Volatile Memory Forensic Analysis in Windows 10 IoT Core

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