###### Abstract  
Due to the rapid development of information and emerging communication technologies, developing and implementing solutions in the Internet of Medical Things (IoMTs) field have become relevant. This work developed a novel data security algorithm for deployment in emerging wireless biomedical sensor network (WBSN) and IoMTs applications while exchanging electronic patient folders (EPFs) over unsecured communication channels. These EFF data are collected using wireless biomedical sensors implemented in WBSN and IoMTs applications. Our algorithm is designed to ensure a high level of security for confidential patient information and verify the copyrights of bio-signal records included in the EPFs. The proposed scheme involves the use of Hahn's discrete orthogonal moments for bio-signal feature vector extraction. Next, confidential patient information with the extracted feature vectors is converted into a QR code. The latter is then encrypted based on a proposed two-dimensional version of the modified chaotic logistic map. To demonstrate the feasibility of our scheme in IoMTs, it was implemented on a low-cost hardware board, namely Raspberry Pi, where the quad-core processors of this board are exploited using parallel computing. The conducted numerical experiments showed, on the one hand, that our scheme is highly secure and provides excellent robustness against common signal-processing attacks (noise, filtering, geometric transformations, compression, etc.). On the other hand, the obtained results demonstrated the fast running of our scheme when it is implemented on the Raspberry Pi board based on parallel computing. Furthermore, the results of the conducted comparisons reflect the superiority of our algorithm in terms of robustness when compared to recent bio-signal copyright protection schemes. biomedical sensors; chaotic system; discrete moments; electronic patient folders; encryption; IoMTs; modified logistic map; WBSNs; zero-watermarking +
Footnote †: journal: Electronics Electronics and Communications Engineering and Technology,  
url
Footnote 1: [[https://www.mdpi.com/journal/electronics/uplo/upl](https://www.mdpi.com/journal/electronics/uplo/upl)]([https://www.mdpi.com/journal/electronics/uplo/upl](https://www.mdpi.com/journal/electronics/uplo/upl))  
the latest information and communication technologies in the healthcare sector [1]. E-health applications include teleraliology [2], telediagnosis [3], teleophthalmology [4], telemedicine [5], image classification via Convolutional Neural Networks (CNN) [6], cell segmentation and tracking [7; 8], face recognition [9], etc. These applications are very promising because they can significantly improve the access, equity, and quality of health services by linking institutions and professionals in the healthcare sector. In addition, they minimize geographical and physical barriers. However, technologies for transmitting and accessing medical information raise critical issues that need to be urgently addressed, including security-related issues [1]. In addition, unauthorized access to private information, such as laboratory tests, pathology history, radiology, physical examinations, etc., can negatively affect patients' privacy [10]. Moreover, medical-related identity crime is a growing threat that already costs billions of dollars each year, and tampering with medical information can put a person's health at risk due to misdiagnosis, delayed treatment, or incorrectly prescribed medications [1]. Healthcare professionals currently exchange electronic patient folders (EPFs) over the Internet worldwide via applications such as telemedicine [11]. An EPF contains information about the patient's health, such as laboratory tests, disease history, radiology, physical examinations, etc. [12]. In addition, the EPF also contains medical images, bio-signals, diagnostic reports, etc. [1]. However, due to the use of many routers when transmitting EPFs via the IoMTs, EPFs become vulnerable to cyber-attacks [13].