Data Hiding Robust to Mobile Communication Vocoders

Abstract

The swift growth of cellular mobile networks in recent years has made voice channels almost accessible everywhere. Besides, data hiding has recently attracted significant attention due to its ability to imperceptibly embed side information that can be used for signal enhancement, security improvement, and two-way authentication purposes. In this regard, we aim at proposing efficient schemes for hiding data in the widespread voice channel of cellular networks. To this aim, our first contribution is to model the channel accurately by considering a linear filter plus a nonlinear scaling function. This model is validated through experiments with true speech signals. Then we leverage on this model to propose two additive and multiplicative data hiding methods based on the spread spectrum techniques. In addition, inspired by the concept of M-ary biorthogonal codes, we develop novel schemes that significantly outperform the previous ones. The performance of all the methods that we present is assessed mathematically and cross-validated with simulations. These are later extended to true speech signals where the results evidence an excellent performance as predicted by the theory. Finally, we assess the imperceptibility by means of both subjective and objective benchmarks and show that the perceptual impact of our watermarks is acceptable.