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European Symposium on Research in Computer Security

ESORICS 2013: Computer Security – ESORICS 2013 pp 700–717Cite as

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  2. Computer Security – ESORICS 2013
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Current Events: Identifying Webpages by Tapping the Electrical Outlet

Current Events: Identifying Webpages by Tapping the Electrical Outlet

  • Shane S. Clark18,
  • Hossen Mustafa19,
  • Benjamin Ransford20,
  • Jacob Sorber21,
  • Kevin Fu22 &
  • …
  • Wenyuan Xu19,23 
  • Conference paper
  • 3101 Accesses

  • 41 Citations

Part of the Lecture Notes in Computer Science book series (LNSC,volume 8134)

Abstract

Computers plugged into power outlets leak identifiable information by drawing variable amounts of power when performing different tasks. This work examines the extent to which this side channel leaks private information about web browsing to an observer taking measurements at the power outlet. Using direct measurements of AC power consumption with an instrumented outlet, we construct a classifier that correctly identifies unlabeled power traces of webpage activity from a set of 51 candidates with 99% precision and 99% recall. The classifier rejects samples of 441 pages outside the corpus with a false-positive rate of less than 2%. It is also robust to a number of variations in webpage loading conditions, including encryption. When trained on power traces from two computers loading the same webpage, the classifier correctly labels further traces of that webpage from either computer. We identify several reasons for this consistently recognizable power consumption, including system calls, and propose countermeasures to limit the leakage of private information. Characterizing the AC power side channel may help lead to practical countermeasures that protect user privacy from an untrustworthy power infrastructure.

Keywords

  • Power Consumption
  • Side Channel
  • Background Process
  • Threat Model
  • Parasitic Modulation

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Author information

Authors and Affiliations

  1. University of Massachusetts Amherst, USA

    Shane S. Clark

  2. University of South Carolina, USA

    Hossen Mustafa & Wenyuan Xu

  3. University of Washington, USA

    Benjamin Ransford

  4. Clemson University, USA

    Jacob Sorber

  5. University of Michigan, USA

    Kevin Fu

  6. Zhejiang University, China

    Wenyuan Xu

Authors
  1. Shane S. Clark
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  2. Hossen Mustafa
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  3. Benjamin Ransford
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  4. Jacob Sorber
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  5. Kevin Fu
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  6. Wenyuan Xu
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Editor information

Editors and Affiliations

  1. Information Security Group, University of London, Royal Holloway, TW20 0EX, Egham Hill, Egham, UK

    Jason Crampton & Keith Mayes & 

  2. Center for Secure Information Systems, George Mason University, 4400 University Drive, 22030-4422, Fairfax, VA, USA

    Sushil Jajodia

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Cite this paper

Clark, S.S., Mustafa, H., Ransford, B., Sorber, J., Fu, K., Xu, W. (2013). Current Events: Identifying Webpages by Tapping the Electrical Outlet. In: Crampton, J., Jajodia, S., Mayes, K. (eds) Computer Security – ESORICS 2013. ESORICS 2013. Lecture Notes in Computer Science, vol 8134. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40203-6_39

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  • DOI: https://doi.org/10.1007/978-3-642-40203-6_39

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  • Online ISBN: 978-3-642-40203-6

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