Image Steganalysis System optimization Based on Boundary Samples

作     者：Li-Na Wang Min-Jie Wang Ting-Ting Zhu Qing Dou 

作者机构：Key Laboratory of Aerospace Information Security and Trusted Computing Ministry of EducationWuhan University School of ComputerWuhan University 

出 版 物：《Journal of Harbin Institute of Technology(New Series)》 (哈尔滨工业大学学报（英文版）)

年 卷 期：2014年第21卷第6期

页      面：57-62页

核心收录：

学科分类：0839[工学-网络空间安全] 08[工学] 081201[工学-计算机系统结构] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Sponsored by the National Natural Science Foundation of China(Grant No.61373169 and 61272453) Doctoral Fund of Ministry of Education of China(Grant No.0110141130006) 

主　　题：image steganalysis digital forensics support vector machine(SVM) boundary samples 

摘      要：In the image steganalysis,the training samples often determine the performance of the model when the features and classification are in the same *** the existing research on steganalysis lacks the in-depth study of the classifier s training method which may deeply influence the detection *** paper provides an optimization of universal steganalysis based on the boundary samples classification concerning about image *** paper proposes a strategy of selecting boundary samples in steganalysis and divides the training samples into good samples,poor samples and boundary samples three categories and then chose the optimal threshold to get boundary samples through *** experimental results show the effectiveness of boundary sample,which dramatically improve detection capability especially for the low embedding rate Stego-image.