Entry Wright:2010:USP from tissec.bib

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BibTeX entry

@Article{Wright:2010:USP,
  author =       "Charles V. Wright and Lucas Ballard and Scott E. Coull
                 and Fabian Monrose and Gerald M. Masson",
  title =        "Uncovering Spoken Phrases in Encrypted Voice over {IP}
                 Conversations",
  journal =      j-TISSEC,
  volume =       "13",
  number =       "4",
  pages =        "35:1--35:??",
  month =        dec,
  year =         "2010",
  CODEN =        "ATISBQ",
  DOI =          "https://doi.org/10.1145/1880022.1880029",
  ISSN =         "1094-9224 (print), 1557-7406 (electronic)",
  ISSN-L =       "1094-9224",
  bibdate =      "Wed Jan 12 17:10:07 MST 2011",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tissec.bib",
  abstract =     "Although Voice over IP (VoIP) is rapidly being
                 adopted, its security implications are not yet fully
                 understood. Since VoIP calls may traverse untrusted
                 networks, packets should be encrypted to ensure
                 confidentiality. However, we show that it is possible
                 to identify the phrases spoken within encrypted VoIP
                 calls when the audio is encoded using variable bit rate
                 codecs. To do so, we train a hidden Markov model using
                 only knowledge of the phonetic pronunciations of words,
                 such as those provided by a dictionary, and search
                 packet sequences for instances of specified phrases.
                 Our approach does not require examples of the speaker's
                 voice, or even example recordings of the words that
                 make up the target phrase. We evaluate our techniques
                 on a standard speech recognition corpus containing over
                 2,000 phonetically rich phrases spoken by 630 distinct
                 speakers from across the continental United States. Our
                 results indicate that we can identify phrases within
                 encrypted calls with an average accuracy of 50\%, and
                 with accuracy greater than 90\% for some phrases.
                 Clearly, such an attack calls into question the
                 efficacy of current VoIP encryption standards. In
                 addition, we examine the impact of various features of
                 the underlying audio on our performance and discuss
                 methods for mitigation.",
  acknowledgement = ack-nhfb,
  articleno =    "35",
  fjournal =     "ACM Transactions on Information and System Security",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J789",
}

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