Entry Radosavac:2008:AFM from tissec.bib

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BibTeX entry

@Article{Radosavac:2008:AFM,
  author =       "Svetlana Radosavac and George Moustakides and John S.
                 Baras and Iordanis Koutsopoulos",
  title =        "An Analytic Framework for Modeling and Detecting
                 Access Layer Misbehavior in Wireless Networks",
  journal =      j-TISSEC,
  volume =       "11",
  number =       "4",
  pages =        "19:1--19:??",
  month =        jul,
  year =         "2008",
  CODEN =        "ATISBQ",
  DOI =          "https://doi.org/10.1145/1380564.1380567",
  ISSN =         "1094-9224 (print), 1557-7406 (electronic)",
  ISSN-L =       "1094-9224",
  bibdate =      "Tue Aug 5 19:37:22 MDT 2008",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tissec.bib",
  abstract =     "The widespread deployment of wireless networks and hot
                 spots that employ the IEEE 802.11 technology has forced
                 network designers to put emphasis on the importance of
                 ensuring efficient and fair use of network resources.
                 In this work we propose a novel framework for detection
                 of intelligent adaptive adversaries in the IEEE 802.11
                 MAC by addressing the problem of detection of the
                 worst-case scenario attacks. Utilizing the nature of
                 this protocol we employ sequential detection methods
                 for detecting greedy behavior and illustrate their
                 performance for detection of least favorable attacks.
                 By using robust statistics in our problem formulation,
                 we attempt to utilize the precision given by parametric
                 tests, while avoiding the specification of the
                 adversarial distribution. This approach establishes the
                 lowest performance bound of a given Intrusion Detection
                 System (IDS) in terms of detection delay and is
                 applicable in online detection systems where users who
                 pay for their services want to obtain the information
                 about the best and the worst case scenarios and
                 performance bounds of the system. This framework is
                 meaningful for studying misbehavior due to the fact
                 that it does not focus on specific adversarial
                 strategies and therefore is applicable to a wide class
                 of adversarial strategies.",
  acknowledgement = ack-nhfb,
  articleno =    "19",
  fjournal =     "ACM Transactions on Information and System Security",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J789",
  keywords =     "MAC layer; min-max robust detection; protocol
                 misbehavior; wireless networks",
}

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