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Information Hiding by Machine Learning: A Method of Key Generation for Information Extracting Using Neural Network

Kensuke Naoe, Hideyasu Sasaki and Yoshiyasu Takefuji
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Kensuke Naoe: Keio University, Japan
Hideyasu Sasaki: Ritsumeikan University, Japan
Yoshiyasu Takefuji: Keio University, Japan

International Journal of Organizational and Collective Intelligence (IJOCI), 2011, vol. 2, issue 1, 21-48

Abstract: In this paper, the authors propose information hiding by machine learning: a method of key generation for information extracting using neural network. The method consists of three layers for information hiding. First, the proposed method prepares feature extraction keys, which are saved by feature extraction attributes like feature coordinates and the region of frequency coefficients. Second, the proposed method prepares hidden patterns in advance to the embedding procedure as a watermark signal of the target contents. Finally, the proposed method generates information extraction keys by using machine learning to output presented hidden patterns. The proper hidden patterns are generated with the proper information extraction key and feature extraction key. In the experiments, the authors show that the proposed method is robust to high pass filtering and JPEG compression. The proposed method contributes to secure visual information hiding without damaging any detailed data of the target content.

Date: 2011
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Handle: RePEc:igg:joci00:v:2:y:2011:i:1:p:21-48