Reinforcement Learning based Trust framework for MANET Environment

Abstract

Mobile Ad-hoc Networks (MANET) are design and implemented without the need for any infrastructure support. The properties of MANET inherently provide greater challenges in areas like security and reliability. This thesis presents three security protocols which were developed for addressing the MANET security needs. A novel trust calculation methodology and intelligent secure route prediction was designed to an existing MANET routing protocol. These protocols will help to implement a trustworthy MANET, providing a dynamic and secure environment.