DIdM-EIoTD: Distributed Identity Management for Edge Internet of Things (IoT) Devices.

Area of Science:

• Computer Science
• Cybersecurity
• Network Engineering

Background:

• The Internet of Things (IoT) paradigm relies on interconnected smart devices, necessitating robust identity management solutions.
• Traditional identity management systems are inadequate for heterogeneous and resource-constrained edge IoT devices.
• Distributed Ledger Technology (DLT) offers potential for secure and decentralized solutions in IoT.

Purpose of the Study:

• To propose a novel DLT-based distributed identity management architecture specifically for edge IoT devices.
• To ensure secure, trustworthy, and privacy-preserving communication within IoT ecosystems.
• To adapt the model for seamless integration with diverse IoT solutions.

Main Methods:

• Development of a generic, distributed, and decentralized location-based identity management model.
• Comprehensive review of DLT consensus mechanisms relevant to IoT identity management.
• Formal verification using Scyther and SPIN model checker for security and state analysis.
• Performance analysis of DLT deployment in fog and edge layers using FobSim simulation tool.

Main Results:

• The proposed DLT-based architecture provides a secure and decentralized approach to IoT identity management.
• Formal verification confirms the security performance and state validity of the model.
• Simulation results indicate enhanced user data privacy and trustworthy communication capabilities.

Conclusions:

• The novel DLT-based architecture effectively addresses the identity management challenges of edge IoT devices.
• The proposed solution enhances security, privacy, and trustworthiness in IoT communications.
• The location-based model is adaptable and suitable for widespread adoption in various IoT applications.