Privacy of User Data in Networked Urban Infrastructures
Fragkiskos Koufogiannis, Shuo Han, George Pappas

Citation
Fragkiskos Koufogiannis, Shuo Han, George Pappas. "Privacy of User Data in Networked Urban Infrastructures". Talk or presentation, 14, October, 2015; Poster presented at the 2015 TerraSwarm Annual Meeting. .

Abstract
Sensor data from users are becoming more widely used in the operation of urban infrastructures such as the power grid and transportation systems. These sensor data may often relate to sensitive information such as daily activities that users are not willing to share with the public. As a result, preserving user privacy has become an important component to these sensor-rich urban infrastructures. We have studied how to diffuse private data across a network. In the context of social networks, we often wish to reveal more information to our friends than to strangers. Nonetheless, our private information can still be leaked to strangers as our friends spread the private information to their friends. We develop an algorithm that enables private data to be diffused across a network. The algorithm guarantees that no individual user, or a group of users, can harm the privacy guarantees of any other user. We illustrate our algorithm with an example of a Facebook ego-network where a user shares their infection status. We have also studied the problem of privacy-preserving smart metering with the aid of internal energy storage. Through charging and discharging, the energy storage device is capable of altering the real-time energy usage profile and masking distinctive patterns that may be of interest to adversaries. We propose a new information-theoretic metric that can provide event-based privacy guarantees. The new privacy metric is evaluated for the best-effort control policy, which tries to keep the reported energy usage constant through compensation from the storage device. Through simulations, we show that the new privacy metric can be computed numerically and gives a nontrivial privacy guarantee.

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Citation formats

• HTML

  Fragkiskos Koufogiannis, Shuo Han, George Pappas. <a
  href="http://www.terraswarm.org/pubs/635.html"><i>Privacy
  of User Data in Networked Urban
  Infrastructures</i></a>, Talk or presentation, 
  14, October, 2015; Poster presented at the <a
  href="http://terraswarm.org/conferences/15/annual"
  >2015 TerraSwarm Annual Meeting</a>.
  .

• Plain text

  Fragkiskos Koufogiannis, Shuo Han, George Pappas.
  "Privacy of User Data in Networked Urban
  Infrastructures". Talk or presentation,  14, October,
  2015; Poster presented at the <a
  href="http://terraswarm.org/conferences/15/annual"
  >2015 TerraSwarm Annual Meeting</a>.
  .

• BibTeX

  @presentation{KoufogiannisHanPappas15_PrivacyOfUserDataInNetworkedUrbanInfrastructures,
      author = {Fragkiskos Koufogiannis and Shuo Han and George
                Pappas},
      title = {Privacy of User Data in Networked Urban
                Infrastructures},
      day = {14},
      month = {October},
      year = {2015},
      note = {Poster presented at the <a
                href="http://terraswarm.org/conferences/15/annual"
                >2015 TerraSwarm Annual Meeting</a>.
  },
      abstract = {Sensor data from users are becoming more widely
                used in the operation of urban infrastructures
                such as the power grid and transportation systems.
                These sensor data may often relate to sensitive
                information such as daily activities that users
                are not willing to share with the public. As a
                result, preserving user privacy has become an
                important component to these sensor-rich urban
                infrastructures. We have studied how to diffuse
                private data across a network. In the context of
                social networks, we often wish to reveal more
                information to our friends than to strangers.
                Nonetheless, our private information can still be
                leaked to strangers as our friends spread the
                private information to their friends. We develop
                an algorithm that enables private data to be
                diffused across a network. The algorithm
                guarantees that no individual user, or a group of
                users, can harm the privacy guarantees of any
                other user. We illustrate our algorithm with an
                example of a Facebook ego-network where a user
                shares their infection status. We have also
                studied the problem of privacy-preserving smart
                metering with the aid of internal energy storage.
                Through charging and discharging, the energy
                storage device is capable of altering the
                real-time energy usage profile and masking
                distinctive patterns that may be of interest to
                adversaries. We propose a new
                information-theoretic metric that can provide
                event-based privacy guarantees. The new privacy
                metric is evaluated for the best-effort control
                policy, which tries to keep the reported energy
                usage constant through compensation from the
                storage device. Through simulations, we show that
                the new privacy metric can be computed numerically
                and gives a nontrivial privacy guarantee.},
      URL = {http://terraswarm.org/pubs/635.html}
  }
  

Posted by Shuo Han on 2 Oct 2015.
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