Entry Erway:2015:DPD from tissec.bib

Last update: Sun Oct 15 02:58:48 MDT 2017                Valid HTML 3.2!

Index sections

Top | Symbols | Numbers | Math | A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Y | Z

BibTeX entry

@Article{Erway:2015:DPD,
  author =       "C. Chris Erway and Alptekin K{\"u}p{\c{c}}{\"u} and
                 Charalampos Papamanthou and Roberto Tamassia",
  title =        "Dynamic Provable Data Possession",
  journal =      j-TISSEC,
  volume =       "17",
  number =       "4",
  pages =        "15:1--15:??",
  month =        apr,
  year =         "2015",
  CODEN =        "ATISBQ",
  DOI =          "https://doi.org/10.1145/2699909",
  ISSN =         "1094-9224 (print), 1557-7406 (electronic)",
  ISSN-L =       "1094-9224",
  bibdate =      "Fri Apr 24 17:39:52 MDT 2015",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tissec.bib",
  abstract =     "As storage-outsourcing services and resource-sharing
                 networks have become popular, the problem of
                 efficiently proving the integrity of data stored at
                 untrusted servers has received increased attention. In
                 the Provable Data Possession (PDP) model, the client
                 preprocesses the data and then sends them to an
                 untrusted server for storage while keeping a small
                 amount of meta-data. The client later asks the server
                 to prove that the stored data have not been tampered
                 with or deleted (without downloading the actual data).
                 However, existing PDP schemes apply only to static (or
                 append-only) files. We present a definitional framework
                 and efficient constructions for Dynamic Provable Data
                 Possession (DPDP), which extends the PDP model to
                 support provable updates to stored data. We use a new
                 version of authenticated dictionaries based on rank
                 information. The price of dynamic updates is a
                 performance change from $ O(1) $ to $ O(\log n) $ (or $
                 O(n^\epsilon \log n)$) for a file consisting of $n$
                 blocks while maintaining the same (or better,
                 respectively) probability of misbehavior detection. Our
                 experiments show that this slowdown is very low in
                 practice (e.g., 415KB proof size and 30ms computational
                 overhead for a 1GB file). We also show how to apply our
                 DPDP scheme to outsourced file systems and version
                 control systems (e.g., CVS).",
  acknowledgement = ack-nhfb,
  articleno =    "15",
  fjournal =     "ACM Transactions on Information and System Security",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J789",
}

Related entries