16#NEW DIMENSION OF DATA SECURITY USING NEURAL NETWORKS AND NUMERICAL FUNCTIONS

Abstract:

Data hiding, embeds data into digital media for the purpose of identification, annotation, and copyright. New possibilities of digital imaging and data hiding open wide prospects in modern imaging science, content management and secure communications. Our objective is to hide large volumes of data in the host, in a manner that causes minimal perceptual distortion, and is robust to survive benign and malicious attacks, and make sure to hide as much information as possible into the host. In this paper we identify the prospects of the hidden information being detected and introduce a new approach for hiding any text without any embedding, by the method of Multiple key functions and Newton Forward Difference Technique so that it passes unnoticed by the existing stochastic detection techniques. By this approach, the size of the data that can be hidden will be larger than all the size that all the existing techniques support. This approach derives a polynomial function that generates the bit position in the host where the data bits matches with the host bits. Since the approach uses the original bits of the host to hide the data, the conventional embedding is not done and so the host does not undergo any perceptual degradation and thus escapes all the existing stochastic detection techniques.