Mutual learning-based efficient synchronization of neural networks to exchange the neural key

Abstract Synchronization of two neural networks through mutual learning is used to exchange the key over a public channel. In absence weight vector from another party, challenge with synchronization how assess coordination communication parties. There an issue delay in current techniques assessment that has impact on security and privacy synchronization. this paper, complete cluster more efficiently timely, important strategy for assessing presented. To approximately determine degree synchronization, frequency having same output prior iterations used. The hash if both are completely synchronized exactly when certain threshold crossed. improved technique makes absolute between parties using vectors’ value. contrast, existing approaches, communicating who follow proposed approach will detect sooner. This reduces effective geometric likelihood. method, therefore, increases safety protocol exchange. been passed different parametric tests. Simulations process show effectiveness terms cited results paper.