ATM: Automated Trust Management for Mobile Ad-hoc Networks Using Support Vector Machine
Links to Fileshttps://ieeexplore.ieee.org/document/6068451
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Type of Work2 pages
conference papers and proceedings preprints
Citation of Original PublicationWenjia Li, Anupam Joshi, and Tim Finin, ATM: Automated Trust Management for Mobile Ad-hoc Networks Using Support Vector Machine, 12th IEEE International Conference on Mobile Data Management (MDM 2011), DOI: 10.1109/MDM.2011.21
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© 2011 IEEE
mobile ad hoc network
support vector machine
UMBC Ebiquity Research Group
Mobile Ad-hoc NETworks (MANETs) are extremely susceptible to various misbehaviors and a variety of trust management schemes have been proposed to detect and mitigate them. Most schemes rely on a set of pre-defined weights to determine how the extent of each misbehavior is used to evaluate the trustworthiness. However, due to the extremely dynamic nature of MANETs, it is not possible to determine a set of weights that are appropriate for all contexts. In this paper, an Automated Trust Management (ATM) system is described for MANETs that uses a support vector machine classifier to detect malicious MANET nodes. The ATM scheme is resilient to attempts by a malicious MANET node to hide its nature by varying its misbehavior patterns over time. The performance of the ATM scheme is evaluated via an extensive simulation study and compared with existing approaches.