Adaptive Risk Prediction and Anonymous Secured Communication in MANET for Medical Informatics.

Abstract

Location-based services (LBS) and information security is a major concern in communication system.With the increasing popularity of location based services more attention is paid to preserve location information to protect the data. In order to protect and preserve the MANET and location based services, there are various existing location based anonymity protocols such as k-anonymity location based, but these protocols are more overhead due to the dynamic mobility nature of ad-hoc networks. In this paper we proposed an Adaptive Risk Prediction and Anonymous Secured Communication protocol to predict the risk before processing anonymous communication. The proposed protocol estimates the risk against adjacent nodes and estimates the vulnerability paths using hidden markov model and decision tree. The decision tree determines the evidence to identify the trusted paths. The anonymous communication message authentication scheme assigns the anonymous communication and organize the secured authentication scheme. We simulated the network by considering different attacks to determine the efficiency of Adaptive Risk Prediction and Anonymous Secured Communication using NS2 simulator.