Blockchain-Based Decentralized Authentication Model for IoT-Based E-Learning and Educational Environments

In recent times, technology has advanced significantly and is currently being integrated into educational environments to facilitate distance learning and interaction between learners. Integrating the Internet of Things(IoT) into education can facilitate the teaching and learning process and expand the context in which students learn. Nevertheless, learning data is very sensitive and must be protected when transmitted over the network or stored in data centers. Moreover, the identity and the authenticity of interacting students, instructors, and staff need to be verified to mitigate the impact of attacks. However, most of the current security and authentication schemes are
centralized, relying on trusted third-party cloud servers, to facilitate continuous secure communication. In addition, most of these schemes are resource-intensive; thus, security and efficiency issues arise when heterogeneous and resource-limited IoT devices are being used. In this paper, we propose a blockchain-based architecture that accurately identifies and authenticates learners and their IoT devices in a decentralized manner and prevents the unauthorized modification of stored learning records in a distributed university network. It allows students and instructors to easily migrate to and join multiple universities within the network using their identity without the need for user re-authentication. The proposed architecture was tested using
a simulation tool, and measured to evaluate its performance. The simulation results demonstrate the ability of the proposed architecture to significantly increase the throughput of learning transactions (40%), reduce the communication overhead and response time (26%), improve authentication efficiency(27%), and reduce the IoT power consumption (35%) compared to the centralized authentication mechanisms. In addition, the security analysis proves
the effectiveness of the proposed architecture in resisting various attacks and ensuring the security requirements of learning data in the university network.