Bidirectional Associative Memory Neural Network for Data Encryption and Decryption
Kushagra Pandey · International Journal for Research in Applied Science and Engineering Technology · 2018
Successful encryption and decryption of data has been a prime concern for any data transfer application.Data may be unwantedly attacked by a malicious attacker.Usually during data transfer, data in encrypted form along with a key is transferred, if a malicious attacker is able to get the key and is able to figure out the encryption algorithm used, the data no longer remains safe.Making a data encryption/decryption system, where there in no need to feed the encrypted data along with the key during data transfer, where key dynamically changes, can make our system more resistant to attackers.Block ciphers with symmetric key encryption are a well know technique for data encryption.A neuro block cipher can be established using recurrent neural networks to develop an encryption system with a dynamically changing key.Neuro recurrent networks can be researched to provide a new edge to network security.