Distortion Compensated Lookup-Table Embedding: Joint Security and Robustness Enhancement for Quantization Based Data Hiding

摘要

Data embedding mechanism used for authentication applications should be secure in order to prevent an adversary from forging the embedded data at his/her will. Meanwhile, semi-fragileness is often preferred to allow for distinguishing content changes versus non-content changes. In this paper, we focus on jointly enhancing the robustness and security of the embedding mechanism, which can be used as a building block for authentication. The paper presents analysis showing that embedding through a look-up table (LUT) of non-trivial run that maps quantized multimedia features randomly to binary data offers a probability of detection error considerably smaller than that of the traditional quantization embedding. We quantify the security strength of LUT embedding and enhance its robustness through distortion compensation. We introduce a combined security and capacity measure and show that the proposed distortion compensated LUT embedding provides joint enhancement of security and robustness over the traditional quantization embedding.