Securing self-configuring Internet of Things (IoT) ecosystem

  • Oluwashina Ajayi

Student thesis: Doctoral Thesis


The scale of the Internet of Things (IoT) systems has expanded over the years, with IoT devices and their ecosystem now becoming an integral part of many information systems. However, the adoption of IoT, which continues to rise, has also led to increased vulnerabilities that can cause users and organisations severe loss and damage when exploited by cybercriminals. Therefore, the quest to provide a secure solution has attracted the research community's interest. Besides, the need for constant availability requires that IoT solutions become Self-configured. In addition to availability, which is an element of a secure solution, confidentiality and integrity of the IoT Ecosystem are essential to keep it from cyber-attacks resulting from the current vulnerabilities within the IoT Systems. There have been several representations of IoT in terms of use cases with security provided in one way or another without fully considering the triage of security – Confidentiality, Integrity, and Availability (CIA).

This thesis first examined the existing solutions to secure the IoT ecosystem. Then, the gaps were identified to give direction to this research by exploring Edge Computing and Distributed Ledger Technology (DLT) capabilities. Finally, an architecture based on Edge Computing and DLT was designed, developed, and implemented to secure the IoT ecosystem and address the gaps identified. This three-layered architecture used EdgeX Foundry and Hyperledger Ledger Fabric as Edge Computing and DLT platforms, respectively. Both EdgeX Foundry and Hyperledger Fabric are enterprise-grade platforms jointly used as an Edge-Blockchain architecture for the first time to provide security within IoT ecosystem.

These architecture's cores were four microservices and message bus designed and developed to provide effective and secure data communication. Furthermore, all security elements and steps to maintain the IoT devices' capabilities and identities within the architecture were presented in this thesis. To further ensure availability, resilience, and robustness and to improve the security of the architecture, a self-configured system algorithm called Scheduler-Based PSO was proposed, developed, and implemented as a Particle Swarm Optimisation(PSO) like algorithm. This algorithm was implemented within themicroservice and applied to a use-case within the Smart-Home environment. This use-case is called the Automatic Temperature Regulated in Augmented Assisted Living (ATRAAL), which provides redundant temperature sensors that can automatically switch over when the primary temperature sensors fail. ATRAAL was conceived as an intervention within an elderly home where mobility is often limited.

In addition, the security features implemented within the Edge-Blockchain architecture were further presented, with adequate evaluation performed for vulnerability. The vulnerability assessment results were compared with the Common Vulnerability Scoring System (CVSS), and a score of 2.7 obtained was "Low" when compared with the CVSS v3.1 vulnerability rating. This thesis has four major studies, each presented as an independent chapter alongside the approach, evaluation, and results. Finally, the work presented in this thesis was provided as a Proof of Concept (PoC) in addressing the gaps identified within the IoT ecosystem. This PoC presents the viability of this research as an approach to secure future IoT systems.
Date of AwardFeb 2023
Original languageEnglish
SponsorsInvest NI
SupervisorMatias Garcia-Constantino (Supervisor), Jose Santos (Supervisor), Joseph Rafferty (Supervisor) & Zhan Cui (Supervisor)


  • Distributed ledger technology
  • Edge computing
  • Blockchain
  • Internet of Things (IoT)

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