# A Medical Image Encryption Scheme for Secure Fingerprint-Based Authenticated Transmission
## 1 Introduction  
In healthcare systems, artificial intelligence (AI) and machine learning (ML) approaches are increasingly used to support physicians in a variety of scenarios, such as the early detection of neurodegenerative disease [1; 2; 3; 4] or cancer early detection in medical images [5; 6; 7]. Medical images are collected through techniques like computed tomography, ultrasound scanning, X-ray, magnetic resonance imaging, and positron emission tomography [8]. The anonymization or pseudonymization of the medical images is insufficient to ensure the patient's privacy [9; 10] and presents various limitations. The anonymized data cannot easily be corrected or augmented by adding other patient information that is subsequently available [11]. Moreover, physicians share medical images and other medical information, such as the Electronic Health Record (EHR), through the hospital intranet or the internet in telemedicine [12]. The secure transmission of medical images and medical information is an essential requirement in healthcare systems, both for training a centralized AI model and for telemedicine applications. During transmission, an attacker could intercept and modify the medical images and EHR to compromise the diagnosis process [13] or the patient's privacy. Therefore, it is necessary to ensure medical data'sintegrity, authenticity, and confidentiality during transmission. Digital watermarking is a technique that provides high data integrity and confidentiality for multimedia data. Digital watermarking involves embedding the image to be hidden in a non-significant reference image. The embedded watermark has imperceptible and robust properties that prevent it from being intentionally altered and visible to the naked eye [14]. However, the watermark approaches are not robust to white-box attacks because the embedded watermarked image is easily retrieved if an attacker is knowledgeable about the watermarking process applied. In addition, the authenticity of transmitted data is another security requirement that a medical image transmission scheme must have. Digital signatures, or blockchains, are commonly used to ensure the authenticity of data transmission over the Internet [15; 16; 17; 18]. However, these approaches are economically and computationally costly, and they require the presence of a dedicated infrastructure. Biometric authentication is an innovative approach to ensuring the authenticity of data without the need for an exchange of keys between parties, as in digital signatures, or dedicated infrastructure, as in blockchains. Biometric data is unique, does not need to be generated at each transmission, and is extremely difficult to replicate by an attacker. Secure medical watermarking with a biometric authentication scheme has been proposed to solve the previous security and implementation issues. A physician's fingerprint has been used in the proposed scheme to ensure authenticity in medical image transmission. In the proposed scheme, a Singular Value Decomposition (SVD) has been applied to the medical image to obtain two unitary matrixes and a singular value vector. The two unitary matrixes have been embedded into two sub-bands of the reference image achieved by the 2D Discrete Wavelet Transform (2D-DWT). The singular value vector has been protected, along with the fingerprint feature vector, by a chaotic encryption scheme based on a random permutation key. It consists of mapping the singular value vector and the fingerprint feature vector into two random matrices achieved by the QR decomposition of a reference image sub-band. Subsequently, the mapped vectors are permuted and embedded into another reference image sub-band following the random permutation key. The random permutation key has been protected through a hybrid asymmetric cryptography scheme based on Elliptic Curve Cryptography (ECC) and Advanced Encryption Standard (AES) algorithms.