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

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

Scalable Lightweight Blockchain-Based Authentication Mechanism for Secure VoIP Communication

Currently, the world is experiencing a global pandemic due to the spread of coronavirus disease 2019 (COVID-19), a disease stemming from a novel coronavirus. The main measure used to contain the rapid spread and to control this virus’s contamination rate is social distancing. This method has dramatically affected citizens’ daily lives. To this end, replacing face-to-face meetings with virtual meetings using cloud videoconferencing application solutions has emerged. This approach has indeed solved this problem for millions of schools, companies, governments, and individuals worldwide. However, security and privacy concerns arise. The number of videoconferencing users has increased during the pandemic, yet some applications offer only unencrypted communication for unpaid users. Moreover, uninvited attendees can join virtual meetings, collect sensitive information about users and shared files, and participate in them using deepfake tools. To resolve this dilemma, we propose in this paper a lightweight, scalable blockchain-based authentication mechanism to secure cloud videoconferencing. Private blockchain, as a decentralized network, can handle user authentication and provide complete data privacy to shared information in a virtual meeting. Moreover, to reduce the latency and mining processing overhead and for scalability of the system, we use a time-based consensus algorithm. Our simulation shows very low latency results, perfect for a video system © 2022, Human-centric Computing and Information Sciences.All Rights Reserved.