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Forensic Analysis of Microsoft Teams: Investigating Memory, Disk and Network

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Science and Technologies for Smart Cities (SmartCity 360 2021)

Abstract

Videoconferencing applications have seen a jump in their userbase owing to the COVID-19 pandemic. The security of these applications has certainly been a hot topic since millions of VoIP users’ data is involved. However, research pertaining to VoIP forensics is still limited to Skype and Zoom. This paper presents a detailed forensic analysis of Microsoft Teams, one of the top 3 videoconferencing applications, in the areas of memory, disk-space and network forensics. Extracted artifacts include critical user data, such as emails, user account information, profile photos, exchanged (including deleted) messages, exchanged text/media files, timestamps and Advanced Encryption Standard encryption keys. The encrypted network traffic is investigated to reconstruct client-server connections involved in a Microsoft Teams meeting with IP addresses, timestamps and digital certificates. The conducted analysis demonstrates that, with strong security mechanisms in place, user data can still be extracted from a client’s desktop. The artifacts also serve as digital evidence in the court of Law, in addition to providing forensic analysts a reference for cases involving Microsoft Teams.

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Acknowledgment

This study is supported with research funds from Research Incentive Funds (R19044) and Provost Research Fellowship Award (R20093), Zayed University, United Arab Emirates.

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Correspondence to Zainab Khalid .

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© 2022 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Khalid, Z., Iqbal, F., Al-Hussaeni, K., MacDermott, A., Hussain, M. (2022). Forensic Analysis of Microsoft Teams: Investigating Memory, Disk and Network. In: Paiva, S., et al. Science and Technologies for Smart Cities. SmartCity 360 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 442. Springer, Cham. https://doi.org/10.1007/978-3-031-06371-8_37

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  • DOI: https://doi.org/10.1007/978-3-031-06371-8_37

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-06370-1

  • Online ISBN: 978-3-031-06371-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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