Citation
Shuo Han. "A Theory of Privacy for Cyber-Physical Systems with Applications in Energy Systems". Talk or presentation, 13, October, 2015.

Abstract
As many cyber-physical systems start to rely on collecting user data for more efficient operation, privacy has emerged as a concern among participating users. In this talk, I will discuss two frameworks that formalize the notion of privacy (differential privacy and information-theoretic privacy) from a unified point of view based on detection theory. I will demonstrate the applications of the two frameworks in energy systems through two case studies. (i) Private distributed charging of electric vehicles: It has been shown that the (non-private) distributed charging problem can be solved using distributed gradient descent. However, the messages exchanged between the center mediator and users may be exploited to breach the privacy of users. We show that differential privacy can be preserved by introducing additive noise to the gradients. We also quantify the trade-off between the level of privacy and the loss of utility using tools from optimization theory. (ii) Private smart metering with internal energy storage: We propose a new information-theoretic metric of privacy in order to handle the privacy of events (e.g., energy usage within any given time slot). The new metric is used to analyze the privacy of a smart metering system that uses internal energy storage as a buffer to hide distinctive energy usage patterns. The results quantify how the amount of energy storage helps improve the level of privacy.

Electronic downloads

• seminar.2015-10-13.Shuo_Han.pdf · application/pdf · 2114 kbytes

• HTML

  Shuo Han. <a
  href="http://chess.eecs.berkeley.edu/pubs/1143.html"
  ><i>A Theory of Privacy for Cyber-Physical Systems
  with Applications in Energy Systems</i></a>,
  Talk or presentation,  13, October, 2015.

• Plain text

  Shuo Han. "A Theory of Privacy for Cyber-Physical
  Systems with Applications in Energy Systems". Talk or
  presentation,  13, October, 2015.

• BibTeX

  @presentation{Han15_TheoryOfPrivacyForCyberPhysicalSystemsWithApplications,
      author = {Shuo Han},
      title = {A Theory of Privacy for Cyber-Physical Systems
                with Applications in Energy Systems},
      day = {13},
      month = {October},
      year = {2015},
      abstract = {As many cyber-physical systems start to rely on
                collecting user data for more efficient operation,
                privacy has emerged as a concern among
                participating users. In this talk, I will discuss
                two frameworks that formalize the notion of
                privacy (differential privacy and
                information-theoretic privacy) from a unified
                point of view based on detection theory. I will
                demonstrate the applications of the two frameworks
                in energy systems through two case studies. (i)
                Private distributed charging of electric vehicles:
                It has been shown that the (non-private)
                distributed charging problem can be solved using
                distributed gradient descent. However, the
                messages exchanged between the center mediator and
                users may be exploited to breach the privacy of
                users. We show that differential privacy can be
                preserved by introducing additive noise to the
                gradients. We also quantify the trade-off between
                the level of privacy and the loss of utility using
                tools from optimization theory. (ii) Private smart
                metering with internal energy storage: We propose
                a new information-theoretic metric of privacy in
                order to handle the privacy of events (e.g.,
                energy usage within any given time slot). The new
                metric is used to analyze the privacy of a smart
                metering system that uses internal energy storage
                as a buffer to hide distinctive energy usage
                patterns. The results quantify how the amount of
                energy storage helps improve the level of privacy.},
      URL = {http://chess.eecs.berkeley.edu/pubs/1143.html}
  }
  

Posted by Sadigh Dorsa on 20 Oct 2015.
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