Anomaly Recognition in Wireless Ad-hoc Network by using Ant Colony Optimization and Deep Learning

As a result of lower initial investment, greater portability, and operational expenses, wireless networks are rapidly replacing their wired counterparts. The new technology that is on the rise Mobile Ad-Hoc Network (MANET), which operates without fixed network infrastructure, can change its topology fly, requires no centralised administration to manage individual nodes. result, MANETs must focus efficiency safety. It crucial in MANET pay attention outliers may affect QoS settings. Nonetheless, despite numerous studies devoted anomaly detection MANET, security breaches performance difficulties keep coming back. There an increased need provide strategies approaches help be more safe robust due wide variety challenges MANET. This study presents outlier for addressing with special identification. suggested work utilises dynamic threshold tackle MANETs, taking into account metrics such as end-to-end delay, jitter, throughput, packet drop, energy usage.