摘要
With the development of the internet of medical things(IoMT),the privacy protection problem has become more and more critical.In this paper,we propose a privacy protection scheme for medical images based on DenseNet and coverless steganography.For a given group of medical images of one patient,DenseNet is used to regroup the images based on feature similarity comparison.Then the mapping indexes can be constructed based on LBP feature and hash generation.After mapping the privacy information with the hash sequences,the corresponding mapped indexes of secret information will be packed together with the medical images group and released to the authorized user.The user can extract the privacy information successfully with a similar method of feature analysis and index construction.The simulation results show good performance of robustness.And the hiding success rate also shows good feasibility and practicability for application.Since the medical images are kept original without embedding and modification,the performance of crack resistance is outstanding and can keep better quality for diagnosis compared with traditional schemes with data embedding.
基金
This work was supported in part by the National Natural Science Foundation of China under Grant 61772561,author J.Q,http://www.nsfc.gov.cn/
in part by the Key Research and Development Plan of Hunan Province under Grant 2018NK2012,author J.Q,and 2019SK2022,author H.T,http://kjt.hunan.gov.cn/
in part by the Science Research Projects of Hunan Provincial Education Department under Grant 18A174,author X.X,and Grant 19B584,author Y.T,http://kxjsc.gov.hnedu.cn/
in part by the Degree&Postgraduate Education Reform Project of Hunan Province under Grant 2019JGYB154,author J.Q,http://xwb.gov.hnedu.cn/
in part by the National Natural Science Foundation of Hunan under Grant 2019JJ50866,author L.T,2020JJ4140,author Y.T,and 2020JJ4141,author X.X,http://kjt.hunan.gov.cn/
in part by the Postgraduate Excellent teaching team Project of Hunan Province under Grant[2019]370-133,author J.Q,http://xwb.gov.hnedu.cn/
and in part by the Postgraduate Education and Teaching Reform Project of Central South University of Forestry&Technology under Grant 2019JG013,author X.X,http://jwc.csuft.edu.cn/.
