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IoT devices, however, are resource-constrained in terms of computing, memory, storage, networking, and energy, making it challenging to secure them properly. In this sense, a lot of work has gone into addressing the security of IoT networks, mostly using classic cryptographic algorithms. The solutions are ML models using backpropagation neural networks to perform network optimization of the network and reduce the overhead consumption as well as increase the network lifetime. The paper highlights ECC's use across a broad range of authentication systems and investigates its potential. They also mitigate attacks and enable IoT security systems to make adjustments in changing environments as per the requirements. In the proposed scheme, we reduce the network errors and a more resistant authentication scheme.