Li, WenjiaJoshi, AnupamFinin, Tim2018-11-152018-11-152011-06-06Wenjia 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.2011.2110.1109/MDM.2011.21http://hdl.handle.net/11603/1199412th IEEE International Conference on Mobile Data Management (MDM 2011)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.2 pagesen-USThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.© 2011 IEEEsecuritytrust managementmobile ad hoc networksupport vector machineUMBC Ebiquity Research GroupText