Learning Representations for Steganalysis from Regularized CNN Model with Auxiliary Tasks

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	Learning Representations for Steganalysis from Regularized CNN Model with Auxiliary Tasks
	Qian, Yinlong; Dong, Jing; Wang, Wei; Tan, Tieniu
	2015
会议名称	International Conference on Communications, Signal Processing, and Systems
会议录名称	Proceedings of International Conference on Communications, Signal Processing, and Systems
会议日期	Oct. 23-24, 2015
会议地点	Chengdu, China
摘要	The key challenge of steganalysis is to construct effective feature representations. Traditional steganalysis systems rely on hand-designed feature extractors. Recently, some efforts have been put toward learning representations automatically using deep models. In this paper, we propose a new CNN based framework for steganalysis based on the concept of incorporating prior knowledge from auxiliary tasks via transfer learning to regularize the CNN model for learning better representations. The auxiliary tasks are generated by computing features that capture global image statistics which are hard to be seized by the CNN network structure. By detecting representative modern embedding methods, we demonstrate that the proposed method is effective in improving the feature learning in CNN models.
关键词	Steganalysis Regularized Cnn
文献类型	会议论文
条目标识符	http://ir.ia.ac.cn/handle/173211/12307
专题	模式识别实验室
通讯作者	Dong, Jing
作者单位	Center for Research on Intelligent Perception and Computing, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences
第一作者单位	模式识别国家重点实验室
通讯作者单位	模式识别国家重点实验室
推荐引用方式 GB/T 7714	Qian, Yinlong,Dong, Jing,Wang, Wei,et al. Learning Representations for Steganalysis from Regularized CNN Model with Auxiliary Tasks[C],2015.

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