DHT- and blockchain-based smart identification for video conferencing

Abstract

Video conferencing applications help people communicate via the Internet and provide a significant and consistent basis for virtual meetings. However, integrity, security, identification, and authentication problems are still universal. Current video conference technologies typically rely on cloud systems to provide a stable and secure basis for executing tasks and processes. At the same time, video conferencing applications are being migrated from centralized to decentralized solutions for better performance without the need for third-party interactions. This article demonstrates a decentralized smart identification scheme for video conferencing applications based on biometric technology, machine learning, and a decentralized hash table combined with blockchain technology. We store users' information on a distributed hash table and transactional events on the distributed ledger after identifying users by implementing machine learning functions. Furthermore, we leverage distributed ledger technology's immutability and traceability properties and distributed hash table unlimited storage feature to improve the system's storage capacity and immutability by evaluating three possible architectures. The experimental results show that an architecture based on blockchain and distributed hash table has better efficiency but needs a longer time to execute than the two other architectures using a centralized database.