JPEG Steganalysis Based on Multi-Projection Ensemble Discriminant Clustering

Yan SUN  Guorui FENG  Yanli REN  

IEICE TRANSACTIONS on Information and Systems   Vol.E102-D    No.1    pp.198-201
Publication Date: 2019/01/01
Publicized: 2018/10/15
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2018EDL8073
Type of Manuscript: LETTER
Category: Information Network
JPEG steganalysis,  multi-projection,  linear discriminant analysis,  K-means,  

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In this paper, we propose a novel algorithm called multi-projection ensemble discriminant clustering (MPEDC) for JPEG steganalysis. The scheme makes use of the optimal projection of linear discriminant analysis (LDA) algorithm to get more projection vectors by using the micro-rotation method. These vectors are similar to the optimal vector. MPEDC combines unsupervised K-means algorithm to make a comprehensive decision classification adaptively. The power of the proposed method is demonstrated on three steganographic methods with three feature extraction methods. Experimental results show that the accuracy can be improved using iterative discriminant classification.