Entry Ciriani:2010:CFE from tissec.bib

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BibTeX entry

@Article{Ciriani:2010:CFE,
  author =       "Valentina Ciriani and Sabrina {De Capitani Di
                 Vimercati} and Sara Foresti and Sushil Jajodia and
                 Stefano Paraboschi and Pierangela Samarati",
  title =        "Combining fragmentation and encryption to protect
                 privacy in data storage",
  journal =      j-TISSEC,
  volume =       "13",
  number =       "3",
  pages =        "22:1--22:??",
  month =        jul,
  year =         "2010",
  CODEN =        "ATISBQ",
  DOI =          "https://doi.org/10.1145/1805974.1805978",
  ISSN =         "1094-9224 (print), 1557-7406 (electronic)",
  ISSN-L =       "1094-9224",
  bibdate =      "Wed Jul 28 14:57:15 MDT 2010",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tissec.bib",
  abstract =     "The impact of privacy requirements in the development
                 of modern applications is increasing very quickly. Many
                 commercial and legal regulations are driving the need
                 to develop reliable solutions for protecting sensitive
                 information whenever it is stored, processed, or
                 communicated to external parties. To this purpose,
                 encryption techniques are currently used in many
                 scenarios where data protection is required since they
                 provide a layer of protection against the disclosure of
                 personal information, which safeguards companies from
                 the costs that may arise from exposing their data to
                 privacy breaches. However, dealing with encrypted data
                 may make query processing more expensive.\par

                 In this article, we address these issues by proposing a
                 solution to enforce the privacy of data collections
                 that combines data fragmentation with encryption. We
                 model privacy requirements as confidentiality
                 constraints expressing the sensitivity of attributes
                 and their associations. We then use encryption as an
                 underlying (conveniently available) measure for making
                 data unintelligible while exploiting fragmentation as a
                 way to break sensitive associations among attributes.
                 We formalize the problem of minimizing the impact of
                 fragmentation in terms of number of fragments and their
                 affinity and present two heuristic algorithms for
                 solving such problems. We also discuss experimental
                 results, comparing the solutions returned by our
                 heuristics with respect to optimal solutions, which
                 show that the heuristics, while guaranteeing a
                 polynomial-time computation cost are able to retrieve
                 solutions close to optimum.",
  acknowledgement = ack-nhfb,
  articleno =    "22",
  fjournal =     "ACM Transactions on Information and System Security",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J789",
  keywords =     "encryption; fragmentation; Privacy",
}

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