An TPM Based Approach for Generation of Secret Key

Abstract

As the world becoming so much internet dependent and near about all the communications are done via internet, so the security of the communicating data is to be enhanced accordingly. For these purpose many encryption-decryption algorithms are available and many neural network based keys are also available which is used in these algorithms. Neural Network is a technique which is designed to work like a human brain. It has the ability to perform complex calculations with ease. To generate a secret key using neural networks many techniques are available like Tree Parity Machine (TPM) and many others. In TPM there are some flaws like less randomness, less time efficient. There are already three rules available i.e. Hebbian Rule, Anti Hebbian Rule and Random Walk, with same problems. So to overcome these issues, we propose a new approach based on the same concept(TPM, as Tree-structured Neural Network's execution time is comparatively less than that of the other Neural Networks) which generate random and timeefficient secret key.