Abstract
To select informative features from steganalytic features, a spatial-domain steganalytic feature selection method based on three-way interaction information and Kolmogorov–Smirnov (KS) test is proposed. Three-way interaction information is employed to rank all the features, and KS test is exploited to remove redundant features. Feature selection process of the proposed method is presented as follows: It calculates mutual information between features and the class label and selects the feature with the maximum value. Then, it loops to calculate three-way interaction information among each candidate feature, the previously selected feature and the class label and select the candidate feature with the maximum value. Following that, it calculates KS test between features and compares an obtained parameter with the predefined significance level for eliminating redundant features. To validate the performance of the proposed method, several typical feature ranking methods based on information measure and spatial-domain steganalytic feature selection methods are adopted for performance comparisons. Experimental results demonstrate that the proposed method can achieve better feature selection performance.
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Acknowledgements
The authors would like to thank Jicang Lu and his co-authors and Morteza Darvish Morshedi Hosseini and his co-author for providing their codes.
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This study was funded by the National Natural Science Foundation of China (61771334).
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Gu, X., Guo, J., Wei, H. et al. Spatial-domain steganalytic feature selection based on three-way interaction information and KS test. Soft Comput 24, 333–340 (2020). https://doi.org/10.1007/s00500-019-03910-x
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DOI: https://doi.org/10.1007/s00500-019-03910-x