Optimized S-box and mix-columns for AES architecture for live IP video encryption and decryption by key generation through face recognition

Abstract

This paper proposes an AES based Encryption and Decryption of a live IP video used for security in surveillance systems. Here, the key is generated based on neural networks techniques for facial recognition. Principal component analysis and Eigen vector algorithms are used to extract biometric facial features which are used to train the neural network. At the receiver side, the original video plays only if the user is authenticated or else it plays an encrypted video. This work proposes an AES architecture based on optimizing timing in terms of adding inner and outer pipeline registers for each round and Key Expansions. Further by optimizing the Crypto Multiplication for Mix columns via LUT based approach aid in further optimization in terms of timing. LUT and Pipelined based implementation techniques are optimal for FPGA based implementations. ROM table and pipelining are the two techniques used to implement AES. Result indicates that with the combination of pipelined architecture and Distributed/Split LUT-Pipelined techniques, the encryption has higher throughput and speed.