Double Security Level Protection Based on Chaotic Maps and SVD for Medical Images

Conghuan Ye (), Shenglong Tan, Jun Wang, Li Shi, Qiankun Zuo and Bing Xiong ()
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Conghuan Ye: School of Information Engineering, Hubei University of Economics, Wuhan 430205, China
Shenglong Tan: School of Information Engineering, Hubei University of Economics, Wuhan 430205, China
Jun Wang: School of Information Engineering, Hubei University of Economics, Wuhan 430205, China
Li Shi: School of Information Engineering, Hubei University of Economics, Wuhan 430205, China
Qiankun Zuo: School of Information Engineering, Hubei University of Economics, Wuhan 430205, China
Bing Xiong: School of Computer and Communication Engineering, Changsha University of Science & Technology, Changsha 410114, China

Mathematics, 2025, vol. 13, issue 2, 1-24

Abstract: The widespread distribution of medical images in smart healthcare systems will cause privacy concerns. The unauthorized sharing of decrypted medical images remains uncontrollable, though image encryption can discourage privacy disclosure. This research proposes a double-level security scheme for medical images to overcome this problem. The proposed joint encryption and watermarking scheme is based on singular-value decomposition (SVD) and chaotic maps. First, three different random sequences are used to encrypt the LL subband in the discrete wavelet transform (DWT) domain; then, HL and LH sub-bands are embedded with watermark information; in the end, we obtain the watermarked and encrypted image with the inverse DWT (IDWT) transform. In this study, SVD is used for watermarking and encryption in the DWT domain. The main originality is that decryption and watermark extraction can be performed separately. Experimental results demonstrate the superiority of the proposed method in key spaces ( 10 225 ), PSNR (76.2543), and UACI (0.3329). In this implementation, the following key achievements are attained. First, our scheme can meet requests of different security levels. Second, encryption and watermarking can be performed separately. Third, the watermark can be detected in the encrypted domain. Thus, experiment results and security analysis demonstrate the effectiveness of the proposed scheme.

Keywords: smart healthcare system; medical image security; joint encryption and watermarking; chaotic neural network; privacy protection (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
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