1st International ICST Workshop on Advances in Sensor Networks

Research Article

Distributed Reputation System for Tracking Applications in Sensor Networks

  • @INPROCEEDINGS{10.1109/MOBIQW.2006.361781,
        author={Tanya Roosta and  Marci  Meingast, and  Sastry  Shankar },
        title={Distributed Reputation System for Tracking Applications in Sensor Networks},
        proceedings={1st International ICST Workshop on Advances in Sensor Networks},
        publisher={IEEE},
        proceedings_a={IWASN},
        year={2007},
        month={5},
        keywords={},
        doi={10.1109/MOBIQW.2006.361781}
    }
    
  • Tanya Roosta
    Marci Meingast,
    Sastry Shankar
    Year: 2007
    Distributed Reputation System for Tracking Applications in Sensor Networks
    IWASN
    IEEE
    DOI: 10.1109/MOBIQW.2006.361781
Tanya Roosta1, Marci Meingast,1, Sastry Shankar 1
  • 1: Dept. of Electr. Eng. & Comput. Sci., California Univ., Berkeley, CA

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