AN ANALYSIS OF TRUST IN SMART HOME DEVICES Davide Ferraris PhD - - PowerPoint PPT Presentation

an analysis of trust in smart home devices
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AN ANALYSIS OF TRUST IN SMART HOME DEVICES Davide Ferraris PhD - - PowerPoint PPT Presentation

AN ANALYSIS OF TRUST IN SMART HOME DEVICES Davide Ferraris PhD Student @ University of Malaga, NICS lab Daniel Bastos Senior Researcher @ British Telecom Co-Authors: Dr. Carmen Fernandez Gago, Dr. Fadi El-Moussa, Prof. Javier Lopez 1 21


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AN ANALYSIS OF TRUST IN SMART HOME DEVICES

Davide Ferraris PhD Student @ University of Malaga, NICS lab Daniel Bastos Senior Researcher @ British Telecom Co-Authors: Dr. Carmen Fernandez Gago, Dr. Fadi El-Moussa, Prof. Javier Lopez

21 August 2019 WISA2019 Workshop

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Outline

 Introduction  Motivation  Use Case  Findings  Trust Model  Conclusion

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Introduction (Trust)

Trust is difficult to define because:  “Trust is a multidimensional, multidisciplinary and multifaceted concept” (Yan et al., 2008)

 “The personal, unique and temporal expectation that a trustor places on a trustee regarding the outcome of an interaction between them” (Moyano et al., 2012)

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Introduction (IoT)

 IoT

  • Connection “everywhere”
  • Remote Control
  • Protocols (Many)
  • Low protection
  • Low computation power

 Smart Home security enhanced by Trust

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Motivation

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Use Case

 Smart Home Scenario  Users  IoT Devices

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Findings

 Alexa (Only the owner can see what is going on through the smartphone app)  Google (Too much trust for the connected users, every connected user can see what is going on and can cast commands)  Google (Wi-Fi steal) Anytime the Wi-Fi is not available the device creates a WAP that allow any user to configure it. (Not ownership)  Hue (Some details are revealed in clear: Bridge ID, IP, commands)

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Findings

 Google

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Findings

 Alexa & Hue

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Findings

 Google & Hue

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Trust model

How the system is? Improvements?  Google: Trust in the users, (set-up) security must be improved  Alexa: Less trust in the other users, (set-up) security can be improved  Hue: “Physical” trust, (set-up) good security measure

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Trust Model

 Role: HO, HM, HG, MU  Context: {1,2,3,4}  Score: {0,1,2,3,4,5}  Trust Metric : TM(Role, Context, Score) How it works? Subtraction of Score and Context to decide if a user is allowed to do something.

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Trust Model

 Trust Metric : TM(Role, Context, Score)  Possible values (Negative, Zero, Positive)  Negative (No actions are allowed for the particular context)  Zero (You can only check what is going on)  Positive (You are trusted enough to cast commands)

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Conclusion

 Different trust models related to Alexa, Google and Hue  Improvement is needed  Improvement proposed  Contact: ferraris@uma.es

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Questions?

Thanks to the European Commission, NeCS Project and to the university of Malaga for the opportunity given to me. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 675320. This work reflects only the author’s view and the Research Executive Agency is not responsible for any use that may be made of the information it contains.

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