SECURED AND ADAPTIVE LEARNING BASED ROUTING SCHEME (SALRS) FOR THE SECURED AND RELIABLE ROUTING IN MANET
T. Manjula, B. Anand · Journal of Critical Reviews · 2020
Mobile Ad Hoc Networking (MANET) technology, one among the most demanded arenas of research due to the wandering computation along with the ubiquitous access of information. The security provisions limitations in MANET are one of the strongest barriers to be come across by the researchers. This security limitation barrier is overcome by utilizing recurrent topology change in multi-hop wireless network. The Secured and Adaptive Learning based Routing Scheme (SALRS) is a stratagem to mitigate the random malicious disruption of information transmissions by encompassing protected and trustworthy routing. This research exploits Fuzzy based Particle Swarm Optimization algorithm (FPSO) which is a security enhancing technique accomplished by creating pairs of optimal distinctive public and private key which in turn achieves keys authentication. The optimal distinctive public and private key plays a significant role in MANET security enhancement. Hybrid Genetic Fuzzy Neural Network algorithm (HGNN) is also introduced in this research to ease the communication of data in a rapid manner by means of adopting route selection and key exchange processes. The Proposed technique exhibits greater reliable data transmission by utilizing the protected hop-by-hop routing technique with utmost packet delivery ratio notch.