CONSTRUCTING HIGHLY NONLINEAR BOOLEAN FUNCTIONS USING GENETIC ALGORITHM(DISSERTATION)

Abstract

The modern world relies on the exchange of digital data in various forms (images, videos, texts, gifs etc). The data travels through public channels. These public channels often becomes a play area for hackers. This calls for cryptographic mechanisms which could make the data invulnerable. Several application nowadays use the stream cipher whose strength depends on the underlying Boolean func- tion. In order to avoid linear approximation attacks on the data encrypted by the steam cipher, it becomes important that the underlying Boolean function has high nonlinearity. Although there are several other characteristics required in an ideal Boolean function however one key property is the nonlinearity of the Boolean function. This thesis is an attempt to construct highly nonlinear Boolean functions using genetic algorithms.