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Smart Home IoT Network Risk Assessment Using Bayesian Networks.

Miguel Flores1, Diego Heredia2, Roberto Andrade3

  • 1Grupo MODES, SIGTI, Facultad de Ciencias, Escuela Politécnica Nacional, Quito 170525, Ecuador.

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Summary
This summary is machine-generated.

This study introduces a Bayesian network model for smart home Internet of Things (IoT) network risk assessment. The model evaluates the impact of Denial of Service (DoS) and Man-in-the-Middle (MitM) attacks on smart home automation devices.

Keywords:
Bayesian networkInternet of Things (IoT)risk assessmentsimulationsmart home

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Area of Science:

  • Cybersecurity
  • Network Security
  • Risk Management

Background:

  • Smart home Internet of Things (IoT) networks are increasingly vulnerable to cyberattacks.
  • Assessing risks in these networks is crucial for protecting automation devices and user data.
  • Existing risk assessment models may not fully capture the complexities of IoT attack vectors.

Purpose of the Study:

  • To develop and implement a Bayesian network-based risk assessment model for smart home IoT networks.
  • To analyze the impact of specific cyberattacks, including Denial of Service (DoS) and Man-in-the-Middle (MitM) attacks.
  • To evaluate the security of smart home automation devices, which often have lower individual security levels.

Main Methods:

  • Constructed a Bayesian network's directed acyclic graph from an attack graph detailing potential attack paths.
  • Estimated Bayesian network parameters using the maximum likelihood method.
  • Applied the model to data from five attack simulation scenarios, considering DoS, MitM, and combined attacks.

Main Results:

  • The Bayesian network model successfully inferred risks associated with various attack scenarios.
  • The model quantified the impact of DoS and MitM attacks on smart home automation devices.
  • Analysis highlighted the heightened vulnerability of devices with inherently lower security levels.

Conclusions:

  • The developed Bayesian network model provides an effective framework for smart home IoT risk assessment.
  • The findings underscore the importance of securing automation devices against common and combined cyber threats.
  • This approach aids in prioritizing security measures for vulnerable IoT components in smart homes.