Entry Brennan:2012:ASC from tissec.bib

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BibTeX entry

@Article{Brennan:2012:ASC,
  author =       "Michael Brennan and Sadia Afroz and Rachel
                 Greenstadt",
  title =        "Adversarial stylometry: Circumventing authorship
                 recognition to preserve privacy and anonymity",
  journal =      j-TISSEC,
  volume =       "15",
  number =       "3",
  pages =        "12:1--12:??",
  month =        nov,
  year =         "2012",
  CODEN =        "ATISBQ",
  DOI =          "https://doi.org/10.1145/2382448.2382450",
  ISSN =         "1094-9224 (print), 1557-7406 (electronic)",
  ISSN-L =       "1094-9224",
  bibdate =      "Wed Nov 28 17:25:14 MST 2012",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tissec.bib",
  abstract =     "The use of stylometry, authorship recognition through
                 purely linguistic means, has contributed to literary,
                 historical, and criminal investigation breakthroughs.
                 Existing stylometry research assumes that authors have
                 not attempted to disguise their linguistic writing
                 style. We challenge this basic assumption of existing
                 stylometry methodologies and present a new area of
                 research: adversarial stylometry. Adversaries have a
                 devastating effect on the robustness of existing
                 classification methods. Our work presents a framework
                 for creating adversarial passages including
                 obfuscation, where a subject attempts to hide her
                 identity, and imitation, where a subject attempts to
                 frame another subject by imitating his writing style,
                 and translation where original passages are obfuscated
                 with machine translation services. This research
                 demonstrates that manual circumvention methods work
                 very well while automated translation methods are not
                 effective. The obfuscation method reduces the
                 techniques' effectiveness to the level of random
                 guessing and the imitation attempts succeed up to 67\%
                 of the time depending on the stylometry technique used.
                 These results are more significant given the fact that
                 experimental subjects were unfamiliar with stylometry,
                 were not professional writers, and spent little time on
                 the attacks. This article also contributes to the field
                 by using human subjects to empirically validate the
                 claim of high accuracy for four current techniques
                 (without adversaries). We have also compiled and
                 released two corpora of adversarial stylometry texts to
                 promote research in this field with a total of 57
                 unique authors. We argue that this field is important
                 to a multidisciplinary approach to privacy, security,
                 and anonymity.",
  acknowledgement = ack-nhfb,
  articleno =    "12",
  fjournal =     "ACM Transactions on Information and System Security",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J789",
}

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