Symmetric Encryption using Artificial Neural Network, Binary Tree Traversal, and Interleaving Salting

We have proposed a novel way of symmetric encryption utilizing interleaving salting, Binary Tree traversal, and an Artificial Neural Network in sequential manner. presented the use as invertible(reversible) mathematical function so that decryption encrypted output may be possible. Knowledge pipeline, salt, neural network weights is required for decryption. As same set values decryption, our approach type symmetric-key algorithm. Each user will unique key. Thus if key attributing to particular compromised, integrity data remaining users still maintained. Our can utilized encrypt text such messages, documents, letters. The process consists creation binary tree by considering input its level order passing preorder inorder traversal constructed Network. would data. Decryption require determining from output, hence solving multiple sets linear equations constructing traversal. then analyzed variation performance with change string size. codebase publicly available at https://github.com/Atishaysjain/Symmetric-Encryption-using-ANN-and-Binary-Trees.