液晶与显示2017，Vol.32Issue(7)：560-566,7.DOI:10.3788/YJYXS20173207.0560
基于贝叶斯分类器的图像隐写分析
Image steganalysis based on bayesian classifier
摘要
Abstract
Recently, ensemble classifier is predominantly used for steganalysis of digital media.For increasing the detection accuracy of ensemble classifier and focused on the defects that the fusion method of ensemble classifier is too simple to reflect the correlation of base learners and can't give an overall result, an algorithm based on Bayesian Classifier is proposed according to a characteristic that the projection of feature on the hyper planes of ensemble classifier obeys the framework of the multivariate Gaussian distribution.At first, some base learners were generated based on the random forest, then the probability density function and prior probability were calculated for training a Bayesian classifier.At last, the algorithm uses a Bayesian Classifier instead of the majority voting rule to fuse the decisions of base learners.The error detection rate lower than before by an average of 1.6%, ROC curve is closer to the top left corner than simple voting method, which has higher detection rate, the growth of AUC value is about 2.12%, and the training time increase about 2.610 s.The proposed method is able to increase steganalysis performance of ensemble classifier.关键词
隐写分析/集成分类器/组合方法/多维正态分布/贝叶斯分类器Key words
steganalysis/ensemble classifier/fusion technique/multivariate Gaussian distribution/Bayesian classifier分类
信息技术与安全科学引用本文复制引用
张兴春,孙寿健..基于贝叶斯分类器的图像隐写分析[J].液晶与显示,2017,32(7):560-566,7.基金项目
国家自然科学基金(No.61403417)Supported by National Natural Science Foundation of China(No.61403417) （No.61403417）
