Reversible Data Hiding Based Key Region Protection Method in Medical Images

被引:0
作者
Li, Jian [1 ]
Zhang, Zelin [1 ]
Li, Shengyu [2 ]
Benton, Ryan [2 ]
Huang, Yulong [3 ]
Kasukurthi, Mohan Vamsi [2 ]
Li, Dongqi [2 ]
Lin, Jingwei [4 ]
Borchert, Glen M. [5 ]
Tan, Shaobo [2 ]
Ma, Bin [1 ]
Yang, Meihong [1 ]
Huang, Jingshan [2 ]
机构
[1] Qilu Univ Technol, Shandong Acad Sci, Shandong Prov Key Lab Comp Networks, Jinan, Peoples R China
[2] Univ S Alabama, Sch Comp, Mobile, AL 36688 USA
[3] Univ S Alabama, Coll Allied Hlth Profess, Mobile, AL USA
[4] Fuzhou Univ, Ocean Sch, Fuzhou, Peoples R China
[5] Univ S Alabama, Dept Pharmacol, Mobile, AL USA
来源
2019 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE (BIBM) | 2019年
基金
中国国家自然科学基金;
关键词
reversible data hiding; key region; QR code; image segmentation; texture complexity; selective encryption;
D O I
10.1109/bibm47256.2019.8983086
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
The transmission of medical image data in an open network environment is subject to privacy issues including patient privacy and data leakage. In the past, image encryption and information-hiding technology have been used to solve such security problems. But these methodologies, in general, suffered from difficulties in retrieving original images. We present in this paper an algorithm to protect key regions in medical images. First, coefficient of variation is used to locate the key regions, a.k.a. the lesion areas, of an image; other areas are then processed in blocks and analyzed for texture complexity. Next, our reversible datahiding algorithm is used to embed the contents from the lesion areas into a high-texture area, and the Arnold transformation is performed to protect the original lesion information. In addition to this, we use the ciphertext of the basic information about the image and the decryption parameter to generate the Quick Response (QR) Code to replace the original key regions. Consequently, only authorized customers can obtain the encryption key to extract information from encrypted images. Experimental results show that our algorithm can not only restore the original image without information loss, but also safely transfer the medical image copyright and patient-sensitive information.
引用
收藏
页码:1526 / 1530
页数:5
相关论文
共 19 条
[1]  
Abdel-Nabi Hiba, 2017, 2017 8th International Conference on Information Technology (ICIT). Proceedings, P802, DOI 10.1109/ICITECH.2017.8079950
[2]  
Arnold V. I., 1970, ZAMM-Z ANGEW MATH ME, V50, P506
[3]   Medical Image Security Using Dual Encryption with Oppositional Based Optimization Algorithm [J].
Avudaiappan, T. ;
Balasubramanian, R. ;
Pandiyan, S. Sundara ;
Saravanan, M. ;
Lakshmanaprabu, S. K. ;
Shankar, K. .
JOURNAL OF MEDICAL SYSTEMS, 2018, 42 (11)
[4]  
Barton J.M., 1997, United States Patent, Patent No. 5646997
[5]  
Brahimi Z., 2008, WSEAS T CIRC SYST, V7, P1
[6]   Lossless generalized-LSB data embedding [J].
Celik, MU ;
Sharma, G ;
Tekalp, AM ;
Saber, E .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2005, 14 (02) :253-266
[7]  
Gurusamy R, 2017, CMC-COMPUT MATER CON, V53, P91
[8]  
Ma B., 2019, SECURITY COMMUNICATI, V2019
[9]  
Ma B., 2016, IEEE T INF FOREN SEC, V11, P1, DOI DOI 10.1109/TIFS.2016.2606958
[10]   A code division multiplexing and block classification-based real-time reversible data-hiding algorithm for medical images [J].
Ma, Bin ;
Li, Bing ;
Wang, Xiao-Yu ;
Wang, Chun-Peng ;
Li, Jian ;
Shi, Yun-Qing .
JOURNAL OF REAL-TIME IMAGE PROCESSING, 2019, 16 (04) :857-869