Biblio

A Network consists of many nodes among which there may be a presence of misbehavior nodes. Delay Tolerant Network (DTN) is a network where the disconnections occur frequently. Store, carry and forward method is followed in DTN. The serious threat against routing in DTN is the selfish behavior. The main intention of selfish node is to save its own energy. Detecting the selfish node in DTN is very difficult. In this paper, a probabilistic misbehavior detection scheme called MAXTRUST has been proposed. Trusted Authority (TA) has been introduced in order to detect the behavior of the nodes periodically based on the task, forwarding history and contact history evidence. After collecting all the evidences from the nodes, the TA would check the inspection node about its behavior. The actions such as punishment or compensation would be given to that particular node based on its behavior. The TA performs probabilistic checking, in order to ensure security at a reduced cost. To further improve the efficiency, dynamic probabilistic inspection has been demonstrated using game theory analysis. The simulation results show the effectiveness and efficiency of the MAXTRUST scheme.

Mobile Ad-hoc Networks are dynamic in nature and do not have fixed infrastructure to govern nodes in the networks. The mission lies ahead in coordinating among such dynamically shifting nodes. The root problem of identifying and isolating misbehaving nodes that refuse to forward packets in multi-hop ad hoc networks is solved by the development of a comprehensive system called Audit-based Misbehavior Detection (AMD) that can efficiently isolates selective and continuous packet droppers. AMD evaluates node behavior on a per-packet basis, without using energy-expensive overhearing techniques or intensive acknowledgment schemes. Moreover, AMD can detect selective dropping attacks even in end-to-end encrypted traffic and can be applied to multi-channel networks. Game theoretical approaches are more suitable in deciding upon the reward mechanisms for which the mobile nodes operate upon. Rewards or penalties have to be decided by ensuring a clean and healthy MANET environment. A non-routine yet surprise alterations are well required in place in deciding suitable and safe reward strategies. This work focuses on integrating a Audit-based Misbehaviour Detection (AMD)scheme and an incentive based reputation scheme with game theoretical approach called Supervisory Game to analyze the selfish behavior of nodes in the MANETs environment. The proposed work GAMD significantly reduces the cost of detecting misbehavior nodes in the network.