Misbehavior Detection Research Articles

An Acknowledgment-Based Approach for the Detection of Routing Misbehavior in MANETs

We study routing misbehavior in MANETs (mobile ad hoc networks) in this paper. In general, routing protocols for MANETs are designed based on the assumption that all participating nodes are fully cooperative. However, due to the open structure and scarcely available battery-based energy, node misbehaviors may exist. One such routing misbehavior is that some selfish nodes will participate in the route discovery and maintenance processes but refuse to forward data packets. In this paper, we propose the 2ACK scheme that serves as an add-on technique for routing schemes to detect routing misbehavior and to mitigate their adverse effect. The main idea of the 2ACK scheme is to send two-hop acknowledgment packets in the opposite direction of the routing path. In order to reduce additional routing overhead, only a fraction of the received data packets are acknowledged in the 2ACK scheme. Analytical and simulation results are presented to evaluate the performance of the proposed scheme

Detecting IEEE 802.11 MAC layer misbehavior in ad hoc networks: Robust strategies against individual and colluding attackers

Selfish behavior at the Medium Access (MAC) Layer can have devastating side effects on the performance of wireless networks, with effects similar to those of Denial of Service (DoS) attacks. In this paper we consider the problem of detection and prevention of node misbehavior at the MAC layer, focu sing on the back-off manipulation by selfish nodes. We first propose an algorithm that ensures honest behavior of non-colluding participants. Furthermore, we analyze the problem of colluding selfish nodes, casting the problem within a minimax robust detection framework and providing an optimal detection rule for the worst-case attack scenarios. Finally, we evaluate the performance of single and colluding attackers in terms of detection delay. Although our approach is general and can be used with any probabilistic distributed MAC protocol, we focus our analysis on the IEEE 802.11 MAC.

Security and Cooperation in clustered mobile ad hoc networks with centralized supervision

Although individual node cooperation is necessary for the correct execution of network protocols in mobile ad hoc networks (MANETs), it is not always guaranteed. In this paper, we present a node reputation scheme aiming at reinforcing node cooperation in MANETs with centralized control. This scheme was designed for centralized ad hoc network architecture (CANA), an ad hoc enhancement to the HIPERLAN/2 WLAN standard. Misbehavior detection techniques for protocol attacks in both the cluster formation and data transmission phases of the network operation are developed. Statistical methods for selecting the optimal parameters of the reputation scheme are investigated and their efficiency is illustrated through theoretical analysis and simulation results. Throughout this paper, the specific aspects of CANA that impose particular design decisions are outlined and the applicability of our scheme to other network architectures is discussed.

An Artificial Immune System Approach With Secondary Response for Misbehavior Detection in Mobile ad hoc Networks

In mobile ad hoc networks, nodes act both as terminals and information relays, and they participate in a common routing protocol, such as dynamic source routing (DSR). The network is vulnerable to routing misbehavior, due to faulty or malicious nodes. Misbehavior detection systems aim at removing this vulnerability. In this paper, we investigate the use of an artificial immune system (AIS) to detect node misbehavior in a mobile ad hoc network using DSR. The system is inspired by the natural immune system (IS) of vertebrates. Our goal is to build a system that, like its natural counterpart, automatically learns, and detects new misbehavior. We describe our solution for the classification task of the AIS; it employs negative selection and clonal selection, the algorithms for learning and adaptation used by the natural IS. We define how we map the natural IS concepts such as self, antigen, and antibody to a mobile ad hoc network and give the resulting algorithm for classifying nodes as misbehaving. We implemented the system in the network simulator Glomosim; we present detection results and discuss how the system parameters affect the performance of primary and secondary response. Further steps will extend the design by using an analogy to the innate system, danger signal, and memory cells.