Detecting malicious nodes in MANET using rateless codes for maximum content distribution

A mobile ad hoc network is a self-organizing infrastructure less network in which collection of mobile nodes are connected by wireless. Security is a major concern in real time mobile environment to provide secured communication. Major problem in wireless network security is data integrity. Existing cryptographic techniques protects the data which can easily be forged by the adversaries. In this paper the pollution attack that modifies the data packet which is easy to launch bogus data inside the network and significantly reduces the network performance. Rateless codes technique is used to encode and decode the data packets, to maintain the integrity of original data. Rateless codes are class of linear error correcting codes and create unlimited number of symbols. The proposed system determines the pollution attack using belief propagation inference technique in order to prevent fake data packets propagate throughout the network. Belief propagation is an iterative process to pass and update the messages until convergence among neighboring variables that allows acting inference on graphical models such as markov random fields, factor graph etc. It is also used to determine the marginal probabilities of all the variables and these estimated marginal probabilities are called as beliefs. The proposed work has been simulated using ns2.35 to evaluate the performance against honest and malicious mobile nodes.