文献类型：期刊文献

英文题名：Steganalysis based on feature reducts of rough set by using genetic algorithm

作者：Dai, Meng[1]; Liu, Yunxiang[1]; Lin, Jiajun[2]

机构：[1] Department of Computer Science and Information Engineering, Shanghai Institute of Technology, Shanghai, 200235, China; [2] Department of Electronic and Communication, East China University of Science and Technology, Shanghai ,200237, China

年份：2008

起止页码：6764

外文期刊名：Proceedings of the World Congress on Intelligent Control and Automation (WCICA)

收录：EI(收录号：20083911600383)

语种：英文

外文关键词：Rough set theory - Steganography

摘要：The supervised learning based statistical detection is generally used in steganalysis. Compared to the specific detecting method, this method has the advantages of flexibility and ability to be quickly adjusted to new or completely unknown steganalytic method. Otherwise, it has the disadvantages in large-scale data, low calculate speed. Knowledge reduction can delete the non-important knowledge while not alter the classification ability of knowledge. While, it is difficult for the original rough set to find out the minimal reduct when dealing with the large-scale and high-attribute data. The GA can solve this matter. It is proved that the speed of the detection system is improved by GA reduction while the ability of classification can be preserved as the formerly level. ? 2008 IEEE.