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PRASH: A Framework for Privacy Risk Analysis of Smart Homes.

Joseph Bugeja1, Andreas Jacobsson1, Paul Davidsson1

  • 1Internet of Things and People Research Center, Department of Computer Science and Media Technology, Malmö University, 21579 Malmö, Sweden.

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Summary
This summary is machine-generated.

We developed PRASH, a framework for analyzing smart home privacy risks. It helps identify and mitigate threats, protecting residents' privacy in connected homes.

Keywords:
IoTattack taxonomyprivacyprivacy metricsrisk analysissmart homesystem modelthreat model

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Area of Science:

  • Computer Science
  • Cybersecurity
  • Human-Computer Interaction

Background:

  • Smart homes offer enhanced living quality but collect sensitive personal data.
  • Protecting user privacy in smart home environments is a critical challenge.
  • Existing methods may not adequately address the complex privacy risks in smart homes.

Purpose of the Study:

  • To introduce PRASH, a novel framework for modeling and analyzing privacy risks in smart homes.
  • To enable early identification and mitigation of privacy threats in smart home systems.
  • To enhance the protection of residents' privacy against potential data breaches and attacks.

Main Methods:

  • PRASH framework comprises a system model, threat model, and privacy metrics.
  • Formal specification is used to represent smart home systems.
  • Executable configurations are generated for analysis and mitigation strategy development.

Main Results:

  • The PRASH framework successfully models smart home privacy risks.
  • Potential attack paths were identified and mitigation strategies were developed.
  • The study demonstrated the framework's capability in analyzing and mitigating privacy impacts.

Conclusions:

  • PRASH provides a robust approach to assessing and managing smart home privacy risks.
  • The framework aids in proactive threat identification and risk mitigation.
  • Implementing PRASH can help preserve user privacy in the evolving smart home landscape.