Team for Research in
Ubiquitous Secure Technology

Citation
Tanya Roosta, Marci Meingast. "Distributed Reputation System for Tracking Applications in Sensor Networks". Talk or presentation, 27, April, 2006; Poster given at Trust NSF Site Visit.

Abstract
Ad-hoc sensor networks are becoming more common, yet security of these networks is still an issue. Node misbehavior due to malicious attacks can impair the overall functioning of the system. Existing approaches mainly rely on cryptography to ensure data authentication and integrity. These approaches only address part of the problem of security in sensor networks. However, cryptography is not sufficient to prevent the attacks in which some of the nodes are overtaken and compromised by a malicious user. Recently, the use of reputation systems has shown positive results as a self-policing mechanism in ad-hoc networks. This scheme can aid in decreasing vulnerabilities which are not solved by cryptography. We look at how a distributed reputation scheme can benefit the object tracking application in sensor networks. Tracking multiple objects is one of the most important applications of the sensor network. In our setup, nodes detect misbehavior locally from observations, and assign a reputation to each of their neighbors. These reputations are used to weight node readings appropriately when performing object tracking. Over time, data from malicious nodes will not be included in the track formation process. We evaluate the reputation system experimentally and demonstrate how it improves object tracking in the presence of malicious nodes

Electronic downloads

• roosta_DistributedReputationSystem_TrustApril06Poster.ppt · application/vnd.ms-powerpoint · 2225 kbytes

• HTML

  Tanya Roosta, Marci Meingast. <a
  href="http://www.truststc.org/pubs/89.html"
  ><i>Distributed Reputation System for Tracking
  Applications in Sensor Networks</i></a>, Talk or
  presentation,  27, April, 2006; Poster given at Trust NSF
  Site Visit.

• Plain text

  Tanya Roosta, Marci Meingast. "Distributed Reputation
  System for Tracking Applications in Sensor Networks".
  Talk or presentation,  27, April, 2006; Poster given at
  Trust NSF Site Visit.

• BibTeX

  @presentation{RoostaMeingast06_DistributedReputationSystemForTrackingApplicationsIn,
      author = {Tanya Roosta, Marci Meingast},
      title = {Distributed Reputation System for Tracking
                Applications in Sensor Networks},
      day = {27},
      month = {April},
      year = {2006},
      note = {Poster given at Trust NSF Site Visit.},
      abstract = {Ad-hoc sensor networks are becoming more common,
                yet security of these networks is still an issue.
                Node misbehavior due to malicious attacks can
                impair the overall functioning of the system.
                Existing approaches mainly rely on cryptography to
                ensure data authentication and integrity. These
                approaches only address part of the problem of
                security in sensor networks. However, cryptography
                is not sufficient to prevent the attacks in which
                some of the nodes are overtaken and compromised by
                a malicious user. Recently, the use of reputation
                systems has shown positive results as a
                self-policing mechanism in ad-hoc networks. This
                scheme can aid in decreasing vulnerabilities which
                are not solved by cryptography. We look at how a
                distributed reputation scheme can benefit the
                object tracking application in sensor networks.
                Tracking multiple objects is one of the most
                important applications of the sensor network. In
                our setup, nodes detect misbehavior locally from
                observations, and assign a reputation to each of
                their neighbors. These reputations are used to
                weight node readings appropriately when performing
                object tracking. Over time, data from malicious
                nodes will not be included in the track formation
                process. We evaluate the reputation system
                experimentally and demonstrate how it improves
                object tracking in the presence of malicious nodes},
      URL = {http://www.truststc.org/pubs/89.html}
  }
  

Posted by Christopher Brooks on 4 May 2006.
Groups: trust
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