Side-Channel Resistance Evaluation of a Neural Network Based Lightweight Cryptography Scheme

Side-channel attacks have changed the design of secure cryptographic systems dramatically. Several published attacks on implementations of well known algorithms such as, e.g., AES, show the need to consider these aspects to build more resistant cryptographic systems. On the other hand, with the increasing use of cryptography in embedded systems a significant demand exists for cryptographic algorithms that are both resource-and power-efficient. These can be either modified existing or completely new ones. One of the candidates for such a new algorithm is the Tree Parity Machine Public Key Exchange, an algorithm based on artificial neural networks. While it has been evaluated in a number of practical applications in the past, its side-channel resistance has not been examined yet. We would like to close this gap and present a side-channel attack strategy as well as results gathered from measurements made on a real implementation.