Affine Neural Network Cryptography - Thada, Vikas; Shrivastava, Utpal (International Journal of Computer Sciences and Engineering, 2025)
In the recent years the main concern in computers and internet has been information security. Researchers and developers are mainly concerned with services which provides secure exchange of information over the internet and networks. The focus has been on 3 security triads: Confidentiality, Integrity, and Availability. The one simple way of achieving security is by the use of cryptography. There are number of features a chaotic systems possess and can be utilized within cryptography. Features like sensitivity to initial conditions/system parameters,ergodicity, mixing properties, deterministic dynamics, and structure complexity. Cryptosystems which are chaos based as compare to conventional provide high levels of security and yields betterresults [2].In this paper a hybrid approach using the concept of affine cipher and chaotic neural network (CNN) is proposed. Data is first encrypted using affine cipher and result of this is fed to the CNN. The reverse operation is performed for decryption. The experiment was carried out in MATLAB 2012a. Secrecy of the proposed work comes from the fact that total four keys need to be kept secret: two from affine and two from CNN. Further the chaos as part of CNN also add to the security.