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Wearable Device Forensic: Probable Case Studies and Proposed Methodology

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Security in Computing and Communications (SSCC 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 969))

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Abstract

Wearable devices have become the face of neoteric technology. What started off as a fashionable trend is gradually becoming an integral part of the user. Devices such as Google Glasses, FitBit, iWatch and other smart watches have been dominating the tech-savvy niche for a while now. The continual real time data collected by wearable devices could be used as forensic evidence to get to an accurate conclusion. Due to the heterogeneous nature of data collected by wearable devices, evidence acquired categorizes into different fields. Data collected by wearable tech of great use in the cracking of cases since it is the closet to the user on a personal level. In certain cases, it has also reduced the time taken to get to the inference. Data collected by these devices that can be utilized for forensics are Geo-location information, Physical and health information of the user, Logs of activities, Account details of Social Media Interaction, Calendar details, Media files, Key Generation Mechanism and Key-Gen logs, etc. This paper details about the practicality of the Digital Forensics of Wearable Devices. A methodology that can be used for the Forensic Analysis has been proposed. The Similarities and the Differences between the Mobile Forensics and Wearable Devices. The Challenges faced during Forensics of Wearable Devices due to ambiguities in present forensic technologies.

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Correspondence to Dhenuka H. Kasukurti .

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Kasukurti, D.H., Patil, S. (2019). Wearable Device Forensic: Probable Case Studies and Proposed Methodology. In: Thampi, S., Madria, S., Wang, G., Rawat, D., Alcaraz Calero, J. (eds) Security in Computing and Communications. SSCC 2018. Communications in Computer and Information Science, vol 969. Springer, Singapore. https://doi.org/10.1007/978-981-13-5826-5_22

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  • DOI: https://doi.org/10.1007/978-981-13-5826-5_22

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-5825-8

  • Online ISBN: 978-981-13-5826-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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