Node misbehavior due to selfish or malicious reasons or faulty nodes can significantly degrade the performance of mobile ad-hoc networks. To cope with misbehavior in such self-organized networks, nodes need to be able to automatically adapt their strategy to changing levels of cooperation. Existing approaches such as economic incentives or secure routing by cryptography alleviate some of the problems, but not all. We describe the use of a self-policing mechanism based on reputation to enable mobile ad-hoc networks to keep functioning despite the presence of misbehaving nodes. The reputation system in all nodes makes them detect misbehavior locally by observation and use of second-hand information. Once a misbehaving node is detected it is automatically isolated from the network. We classify the features of such reputation systems and describe possible implementations of each of them. We explain in particular how it is possible to use second-hand information while mitigating contamination by spurious ratings. In mobile ad-hoc networks, nodes are both routers and terminals. For lack of routing infrastructure, they have to cooperate to communicate. Cooperation at the network layer means routing, i.e., finding a path for a packet, and forwarding, i.e., relaying packets for others. Misbehavior means deviation from regular routing and forwardin. It arises for several reasons, non-intentionally when a node is faulty; Intentional misbehavior can aim at an advantage for the misbehaving node or just constitute vandalism, such as enabling a malicious node to mount an attack or a selfish node to save power. In game-theoretic terms, cooperation in mobile ad-hoc networks poses a dilemma. To save battery, bandwidth, and processing power, nodes should not forward packets for others. If this dominant strategy is adopted, however, the outcome is a non-functional network when multi-hop routes are needed, so all nodes are worse off. Without countermeasures, the effects of misbehavior have been shown to dramatically decrease network performance [2, 9] . Depending on the proportion of misbehaving nodes and their strategies, network throughput decrease, packet loss, denial of service, and network partioning can result.These detrimental effects of mis- * The work presented in this paper was supported (in part) by the National The question we address is the following. How can we make an existing system keep working despite misbehavior? Can one weed out misbehaving nodes? When fewer nodes deviate from the protocol, the network performance is more predictable and less chaotic. The main solutions to address this question are secure routing, economic incentives, and detection and reputation systems. Secure routing using cryptography, such as Ariadne or SRP [6] provides preventive means for specific malicious attacks, e.g. compromising routes. Secure routing applies to route discovery. Once a route is found, its use is not secured. Economic incentives such as payment schemes aim at making selfish nodes forward for others despite the power usage and effort this entails. Nodes are paid for forwarding and pay for the forwarding of their own packets by other nodes. An example are nuglets, a virtual currency, or the credit counter [6] in secure hardware, where nodes keep track of remaining battery power and credit. These approaches make it undesirable for selfish nodes to deny forwarding. They do not, however, target other types of misbehavior. Secure routing and economic incentives solve part of the question, but not all. There remains a variety of observable types of misbehavior that they cannot cure easily, such as silent route changes, which may be addressed by detection and reputation systems. They monitor and rate the behavior of other nodes in routing and forwarding, such that nodes can respond according to their opinion about other nodes. The opinion a node has of another is called reputation. The goal of a reputation system is to enable nodes to make informed decisions about which nodes to cooperate with or exclude from the network. Reputation systems can be used to cope with any kind of misbehavior as long as it is observable. We next describe a framework for detection and reputation systems and list a number of proposed approaches. Then we analyze the main issues and features for reputation systems; we find that these are: representation of information and classification, use of second-hand information, trust, and redemption and secondary response. In separate sections, we discuss how each of these features can be implemented, using one such reputation system as a basis for comparison. We explain in particular how it is possible to use second-hand information while mitigating contamination by spurious ratings. Then we illustrate on some scenarios the types of misbehavior targeting reputation systems.
An overall survey of the reputation system in AD-HOC networks and a more detailed overview has been established in REF .
Self-policing mobile ad hoc networks by reputation systems
IEEE Communications Magazine
Computer Science