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In cryptography, encryption is the process of transforming information referred to as plain-text using an algorithm (called a cipher) to make it unreadable to anyone except those possessing special knowledge, usually referred to as a key. The result of the process is information which is, referred to as cipher-text. Stream ciphers are used to encrypt individual bits. This is achieved by adding a bit from a key stream to a plain-text bit. Generating the key stream is the therefore important. In this paper a soft computing based approach is proposed for generating keys to design a stream cipher for text encryption. Optimal weights for the sender and receiver used for the synchronization on the Tree Parity Machine(TPM) neural network, are generated using a Genetic Algorithm(GA).
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