Image Encryption using 2D Cellular Automata

Abstract

This thesis sums up problems associated with trivial Arnold cat map and 2D Cellular automata scrambling technique. An exploratory study is performed over scrambling of gray scale image using Arnold cat map and 2D Cellular automata’s both variants i.e. Moore neighborhood and Vonneumann neighborhood. Firstly, we scramble the gray scale image using both techniques i.e. Arnold transform and 2D Cellular automata and then make a comparative study about effectiveness of scrambling by both the mentioned techniques, we conclude which technique scrambles image with high scrambling degree measured by scrambling degree parameters GDD and Correlation Coefficient. Later, we focused on improving scrambling degree by using combination of both techniques i.e. Arnold and 2D Cellular automata. For combined technique of scrambling we first scramble image with one of the variant of 2D Cellular automata and then we scramble through Arnold cat map. Further a comparison between individual Arnold and 2D Cellular automata with combined scrambling technique’s performance is obtained. A conclusion is drawn about scrambling degree of this combined technique whether it improves scrambling degree parameters i.e. GDD and Correlation Coefficient than previous methods or not. Apart from improving scrambling degree this combined technique ensures that this scrambling technique doesn’t possess periodicity property even after using Arnold transform while scrambling.