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Toward Cybersecurity Testing and Monitoring of IoT Ecosystems.

Steve Taylor1, Martin Gilje Jaatun2, Aida Omerovic3

  • 1University of Southampton, Southampton, UK.

SN Computer Science
|May 25, 2026
PubMed
Summary

This study introduces a unified architecture for Internet of Things (IoT) cybersecurity, integrating testing, monitoring, and risk modeling across the device lifecycle. It enhances security assurance for complex, interconnected IoT systems.

Keywords:
Cyber physical systemsIoTSecurity monitoringSecurity testingSoftware supply chainSystemic vulnerabilityThreat and risk analysisTool chainsWorkflow

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Area of Science:

  • Cybersecurity Engineering
  • Distributed Systems
  • Risk Management

Background:

  • Internet of Things (IoT) ecosystems face unique cybersecurity challenges due to device diversity, limited resources, and complex integration.
  • Current IoT security solutions often address isolated aspects, lacking lifecycle integration and system-wide context.
  • Systemic vulnerability and risk propagation in interconnected IoT, ICT, and human interactions remain significant concerns.

Purpose of the Study:

  • To present an extensible architecture unifying cybersecurity testing, runtime monitoring, risk modeling, secure updates, and evidence management for IoT ecosystems.
  • To provide a framework supporting both device and system perspectives, integrating component-level and system-level security techniques.
  • To advance lifecycle-integrated, system-aware cybersecurity assurance for complex IoT environments.

Main Methods:

  • Developed an extensible architecture integrating cybersecurity testing, runtime monitoring, contextual risk modeling, secure updates, and auditable evidence management.
  • Employed component-level techniques (SBOM generation, network fuzzing, ML-based anomaly detection) and system-level, knowledge-based risk modeling.
  • Utilized a distributed ledger for data integrity and automated workflow orchestration for lifecycle-aware execution.

Main Results:

  • Demonstrated the feasibility of combining static analysis, runtime indicators, and dynamic risk assessment for contextual vulnerability prioritization.
  • Successfully detected anomalous behavior and supported secure patch deployment in resource-constrained environments.
  • Validated the approach through industrial use cases in aviation cargo monitoring, smart manufacturing, and telecommunication residential gateways.

Conclusions:

  • The proposed architecture effectively unifies diverse cybersecurity measures for comprehensive IoT assurance.
  • Lifecycle-integrated, system-aware approaches are crucial for addressing systemic risks in complex IoT ecosystems.
  • Contextualized, interoperable tooling is essential for managing cybersecurity in environments where IoT, ICT, and people interact.