The Internet of Things (IoT) paradigm aims to enhance human society and living standards with the vast deployment of smart and autonomous devices, which requires seamless collaboration. The number of connected devices increases daily, introducing identity management requirements for edge IoT devices. Due to IoT devices’ heterogeneity and resource-constrained configuration, traditional identity management systems are not feasible. As a result, identity management for IoT devices is still an open issue. Distributed Ledger Technology (DLT) and blockchain-based security solutions are becoming popular in different application domains. This paper presents a novel DLT-based distributed identity management architecture for edge IoT devices. The model can be adapted with any IoT solution for secure and trustworthy communication between devices. We have comprehensively reviewed popular consensus mechanisms used in DLT implementations and their connection to IoT research, specifically identity management for Edge IoT devices. Our proposed location-based identity management model is generic, distributed, and decentralized. The proposed model is verified using the Scyther formal verification tool for security performance measurement. SPIN model checker is employed for different state verification of our proposed model. The open-source simulation tool FobSim is used for fog and edge/user layer DTL deployment performance analysis. The results and discussion section represents how our proposed decentralized identity management solution should enhance user data privacy and secure and trustworthy communication in IoT.

The Internet of things (IoT) will accommodate several billions of devices to the Internet to enhance human society as well as to improve the quality of living. A huge number of sensors, actuators, gateways, servers, and related end-user applications will be connected to the Internet. All these entities require identities to communicate with each other. The communicating devices may have mobility and currently, the only main identity solution is IP based identity management which is not suitable for the authentication and authorization of the heterogeneous IoT devices. Sometimes devices and applications need to communicate in real-time to make decisions within very short times. Most of the recently proposed solutions for identity management are cloud-based. Those cloud-based identity management solutions are not feasible for heterogeneous IoT devices. In this paper, we have proposed an edge-fog based decentralized identity management and authentication solution for IoT devices (IoTD) and edge IoT gateways (EIoTG). We have also presented a secure communication protocol for communication between edge IoT devices and edge IoT gateways. The proposed security protocols are verified using Scyther formal verification tool, which is a popular tool for automated verification of security protocols. The proposed model is specified using the PROMELA language. SPIN model checker is used to confirm the specification of the proposed model. The results show different message flows without any error.

Fog computing-based solution improves the quality of IoT solutions by making a bridge between the cloud layer and end devices of the IoT paradigm. Fog computing can also increase security and trust in IoT by processing data at the fog layer which is closer to the source of data where it is produced. Reproducibility of research results is one of the curtail criteria for any scientific research. Proper documentation about research methodology allows fellow researchers to reproduce the results and to further extend the research findings. Recent researches are addressing fog computing-based trust and security solutions for the resource constraint IoT devices as it is more convenient and efficient to manage those from the nearest location and not managing those from the cloud. In this paper, we have presented the current state of fog computing-based trust solutions for IoT with future research direction within the area. A framework for trust management for IoT at the fog layer is also proposed in this paper. We have also discussed different scientific research approaches used in fog computing-based trust management in IoT research. The strengths and weaknesses of existing research methodologies used in fog computing-based trust management solutions in the internet of things (IoT) research are also discussed.

As programming emerges as a critical skill in the digital age and digital tools continue to evolve, understanding students’ perspectives on the integration of such technologies into their education is crucial. This empirical study explores the perspectives of students in Sweden and Taiwan on the use of digital tools in their programming courses. The research employs both qualitative and quantitative methods, including correlation analysis and inductive content analysis, to understand students’ perceptions of the usefulness and challenges involved in the application of different digital technologies. The study reveals the importance of immediate feedback, visualization of concepts, online discussion platforms, and programming tools’ tutorials. However, concerns about potential bias in AI grading systems and the need for more time and guidance to become familiar with new technologies are also highlighted. The study provides valuable insights that can guide the development of more user-centered tools for supporting programming education.