Enhancing Node Cooperation in Mobile Wireless Ad Hoc Networks with Selfish Nodes

In Mobile Ad Hoc Networks (MANETs), nodes depend on each other for routing and forwarding packets. However, to save power and other resources, nodes belonging to independent authorities may behave selfishly, and may not be willing to help other nodes. Such selfish behavior poses a real threat to the proper functioning of MANETs. One way to foster node cooperation is to introduce punishment for selfish nodes. Based on neighbor-monitoring techniques, a fully distributed solution to detect, punish, and re-admit selfish nodes, is proposed here. This solution provides nodes the same opportunity to serve/and be served by others. A light-weight solution regarding battery status is also proposed here. This solution requires neighbor monitoring only when necessary, thereby saving nodes battery power. Another effective way to solve the selfish-node problem is to reward nodes for their service according to their cost. To force nodes to show their true cost, truthful protocols are needed. A low overhead truthful routing protocol to find optimal routes is proposed in this thesis. The most prominent feature of this protocol is the reduction of overhead from existing solutions O(n3) to O(n2). A light-weight scalable truthful routing protocol (LSTOP) is further proposed, which finds near-least-cost paths in dense networks. LSTOP reduces overhead to O(n) on average, and O(n2) in worst case scenarios. Multiple path routing protocols are an effective alternative to single path routing protocols. A generic mechanism that can turn any table-driven multipath routing protocol into a truthful one, is outlined here. A truthful multipath routing protocol (TMRP), based on well-known AOMDV protocol, is presented as an example. TMRP incurs an only 2n message overhead for a route discovery, and can also achieve load balancing without compromising truthfulness. To cope with the selfish-node problem in the area of position-based routing, a truthful geographic forwarding (TGF) algorithm is presented. TGF utilizes three auction-based forwarding schemes to stimulate node cooperation. The truthfulness of these schemes is proven, and their performance is evaluated through statistical analysis and simulation studies

A NOVEL METHODOLOGY TO OVERCOME ROUTING MISBEHAVIOR IN MANET USING RETALIATION MODEL

ABSTRACT MANET is a cooperative network in which nodes are responsible for forwarding as well as routing. Noncooperation is still a big challenge that certainly degrades the performance and reliability of a MANET. This paper presents a novel methodology to overcome routing misbehavior in MANET using Retaliation Model. In this model node misbehavior is watched and an equivalent misbehavior is given in return. This model employs several parameters such as number of packets forwarded, number of packets received for forwarding, packet forwarding ratio etc. to calculate Grade and Bonus Points. The Grade is used to isolate selfish nodes from the routing paths and the Bonus Points defines the number of packets dropped by an honest node in retaliation over its misconducts. The implementation is done in "GloMoSi

Collaboration Enforcement In Mobile Ad Hoc Networks

Mobile Ad hoc NETworks (MANETs) have attracted great research interest in recent years. Among many issues, lack of motivation for participating nodes to collaborate forms a major obstacle to the adoption of MANETs. Many contemporary collaboration enforcement techniques employ reputation mechanisms for nodes to avoid and penalize malicious participants. Reputation information is propagated among participants and updated based on complicated trust relationships to thwart false accusation of benign nodes. The aforementioned strategy suffers from low scalability and is likely to be exploited by adversaries. To address these problems, we first propose a finite state model. With this technique, no reputation information is propagated in the network and malicious nodes cannot cause false penalty to benign hosts. Misbehaving node detection is performed on-demand; and malicious node punishment and avoidance are accomplished by only maintaining reputation information within neighboring nodes. This scheme, however, requires that each node equip with a tamper-proof hardware. In the second technique, no such restriction applies. Participating nodes classify their one-hop neighbors through direct observation and misbehaving nodes are penalized within their localities. Data packets are dynamically rerouted to circumvent selfish nodes. In both schemes, overall network performance is greatly enhanced. Our approach significantly simplifies the collaboration enforcement process, incurs low overhead, and is robust against various malicious behaviors. Simulation results based on different system configurations indicate that the proposed technique can significantly improve network performance with very low communication cost

Thwarting Sybil Attackers in Reputation-based Scheme in Mobile Ad hoc Networks

Routing in mobile ad hoc networks is performed in a distributed fashion where each node acts as host and router, such that it forwards incoming packets for others without relying on a dedicated router. Nodes are mostly resource constraint and the users are usually inclined to conserve their resources and exhibit selfish behaviour by not contributing in the routing process. The trust and reputation models have been proposed to motivate selfish nodes for cooperation in the packet forwarding process. Nodes having bad trust or reputation are detected and secluded from the network, eventually. However, due to the lack of proper identity management and use of non-persistent identities in ad hoc networks, malicious nodes can pose various threats to these methods. For example, a malicious node can discard the bad reputed identity and enter into the system with another identity afresh, called whitewashing. Similarly, a malicious node may create more than one identity, called Sybil attack, for self-promotion, defame other nodes, and broadcast fake recommendations in the network. These identity-based attacks disrupt the overall detection of the reputation systems. In this paper, we propose a reputation-based scheme that detects selfish nodes and deters identity attacks. We address the issue in such a way that, for normal selfish nodes, it will become no longer advantageous to carry out a whitewash. Sybil attackers are also discouraged (i.e., on a single battery, they may create fewer identities). We design and analyse our rationale via game theory and evaluate our proposed reputation system using NS-2 simulator. The results obtained from the simulation demonstrate that our proposed technique considerably diminishes the throughput and utility of selfish nodes with a single identity and selfish nodes with multiple identities when compared to the benchmark scheme