Deep Learning Multipath Routing for Cyber Security Iot Networks

  • Mr. M. Sabarish, Dr. P. Mayilvahanan

Abstract

SDN is a paradigm shift that modifies the working principles of IP networks by removing control logic from routers and switches and conceptually centralising it into a controller. As SDN networks expand, they become more vulnerable to assaults, necessitating the need for robust security procedures. Because sensor nodes have limited energy, processing capabilities, and storage resources, determining appropriate cryptography for wireless sensor networks is a critical challenge. Novel energy-aware routing algorithms, known as dependable minimal Deep Learning Trust Secure Attacker Detection, will be introduced for Adhoc networks. DLTSAD meets important SDN requirements including energy economy, reliability, data aggregation, and attacker detection. DLTSAD is a low-energy routing approach that generates routes that utilise the least amount of energy for end-to-end packet traversal while also enhancing malicious node detection. To use the encryption approach in SDN, we presented a cryptography-based security mechanism. Improving the encryption and decryption elements of an existing method, which paves the path for better security.

Published
2021-11-30
How to Cite
Mr. M. Sabarish, Dr. P. Mayilvahanan. (2021). Deep Learning Multipath Routing for Cyber Security Iot Networks. Design Engineering, 941 - 959. Retrieved from http://www.thedesignengineering.com/index.php/DE/article/view/7031
Section
Articles