Browsing by Subject "misbehavior detection"
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Item Outlier Detection in Ad Hoc Networks Using Dempster-Shafer Theory(IEEE, 2009-05-18) Li, Wenjia; Joshi, AnupamMobile Ad-hoc NETworks (MANETs) are known to be vulnerable to a variety of attacks due to lack of central authority or fixed network infrastructure. Many security schemes have been proposed to identify misbehaving nodes. Most of these security schemes rely on either a predefined threshold, or a set of well-defined training data to build up the detection mechanism before effectively identifying the malicious peers. However, it is generally difficult to set appropriate thresholds, and collecting training datasets representative of an attack ahead of time is also problematic. We observe that the malicious peers generally demonstrate behavioral patterns different from all the other normal peers, and argue that outlier detection techniques can be used to detect malicious peers in ad hoc networks. A problem with this approach is combining evidence from potentially untrustworthy peers to detect the outliers. In this paper, an outlier detection algorithm is proposed that applies the Dempster-Shafer theory to combine observation results from multiple nodes because it can appropriately reflect uncertainty as well as unreliability of the observations. The simulation results show that the proposed scheme is highly resilient to attackers and it can converge stably to a common outlier view amongst distributed nodes with a limited communication overhead.Item Policy-based Malicious Peer Detection in Ad Hoc Networks(IEEE, 2009-08-29) Li, Wenjia; Joshi, Anupam; Finin, TimMobile Ad hoc Networks (MANETs) are susceptible to various node misbehaviors due to their unique features, such as highly dynamic network topology, rigorous power constraints and error-prone transmission media. Significant research efforts have been made to address the problem of misbehavior detection. However, little research work has been done to distinguish truly malicious behaviors from the faulty behaviors. Both the malicious behaviors and the faulty behaviors are generally equally treated as misbehaviors without any further investigation by most of the traditional misbehavior detection mechanisms. In this paper, we propose and develop a policy-based malicious peer detection mechanism, in which context information, such as communication channel status, buffer status, and transmission power level, is collected and then used to determine whether the misbehavior is likely a result of malicious activity or not. Simulation results illustrate that the policy-based malicious peer