Internet of Things-Based Security Model and Solutions for Educational Systems

Today the applications of Internet of things (IoT) are progressing rapidly in variety of domains. This encouraged to develop new applications (e.g., smart grid, smart home, smart cities, wearables, and vehicle networking) advancement as well. The emerging application of IoT is exposed toward security, privacy issues, and its challenges. The main objective of this work is to enhance security in the educational system (ES) using IoT devices. We propose several techniques to avail device identification, authenticate the user, and collect the data from various devices. As the IoT sensors are easily negotiable, it allows unauthorized users/devices that are able to steal and override the data from the cloud. This paper represents a brief summary of IoT security threats and challenges and their classification based on the application domain. The authors identified challenges in security issues in IoT-based educational systems and some probable solutions on security. In this research, the authors propose the incremental Gaussian mixture model (IGMM), blockchain, and EdgeSec as a probable solution for security and machine learning (ML) techniques. In this model, few solutions, like IGMM for authorizing the device, blockchain for the encryption of data during transfer in the information network, ML algorithms for identifying and authorizing devices, and EdgeSec, offer a security profile to collect a huge amount of data about each device in the connected IoT environment. The identified model is used for enhancing security in IoT-based educational systems. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021.