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Abstract
With the help of big data, cloud computing, artificial intelligence and other technologies, the informatization and intelligence of the wisdom medical have been gradually realized. However, with the transmission and storage of massive amounts of medical images in the cloud, information security issues have become increasingly prominent. The privacy of patients is at risk of disclosure, theft and tampering, which has become an important challenge restricting the development of wisdom medical. How to protect the personal information of patients in the cloud environment has become an urgent problem to be solved. Medical image watermarking technology is an effective method to solve this problem. Combining the characteristics of Tent chaos and Henon chaos, this paper designed a Tent-Henon-Map double chaos watermarking encryption method and designed a medical image encryption watermarking algorithm based on ridgelet-DCT transform. The watermark images were encrypted by the Tent-Henon-Map double chaos which had the characteristics of sensitive initial values and large key space. Then, the feature vectors of the medical images were extracted through ridgelet-DCT transform. On the basis of ordinary watermarking technology, combined with zero watermarking, third-party concepts, and cryptographic technology, watermarking had a good ability to resist image processing attacks. The experimental results showed that the key space of the algorithm was
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Details
1 Hainan University, School of Information and Communication Engineering, Haikou, China (GRID:grid.428986.9) (ISNI:0000 0001 0373 6302); Haikou University of Economics, Haikou, China (GRID:grid.428986.9)
2 Hainan University, School of Information and Communication Engineering, Haikou, China (GRID:grid.428986.9) (ISNI:0000 0001 0373 6302)
3 Ritsumeikan University, College of Information Science and Engineering, Shiga, Japan (GRID:grid.262576.2) (ISNI:0000 0000 8863 9909)
4 Hainan Normal University, School of Mathematics and Statistics, Haikou, China (GRID:grid.440732.6) (ISNI:0000 0000 8551 5345)
5 Research Center for Healthcare Data Science, Hangzhou, China (GRID:grid.440732.6)