This paper provides a summary of our work over the past two years on robust, high-volume data hiding in images. We first present a basic framework for image-adaptive hiding, which allows selection of the coeficients in which to hide, and employs powerful "turbo-like" erasures and errors codes in a novel manner to prevent desynchronization of encoder and decoder due to selective embedding. This coding framework provides robustness against a variety of attacks, including compression, tampering and moderate resizing. Next, we provide a joint source-channel coding scheme for image-in-image hiding, in which the quality of the recovered signature image is better if the attack is milder. This is achieved by hybrid digital-analog hiding. Finally, we present preliminary results on hiding techniques that survive printing and scanning. The techniques are devised after experimental modeling of the print-scan channel.