Protection Of Medical Data Research Articles

Telemedicine and experimental legal regimes in the field of healthcare: problems and prospects for implementation

In connection with the adoption of Federal Law No. 258-FZ of July 31, 2020 “On experimental legal regimes in the field of digital innovation in the Russian Federation,” a number of initiatives have been developed to establish experimental legal regimes in the field of telemedicine. The idea of using digital technologies in medicine is certainly relevant. On the one hand, the prospect of remotely receiving medical services is practically in demand; on the other, the level of technology development currently allows for a significant expansion of their implementation. The need to turn to the institution of an experimental legal regime is due to the fact that the current legislation contains norms that seriously complicate the process of widespread dissemination of telemedicine services.The purpose of the study is to reveal the theoretical characteristics of the concept of telemedicine and its current state, to identify legal obstacles to its development, to conduct a comparative analysis of existing draft programs of experimental regimes, to assess the problems and prospects for the development of telemedicine technologies in modern Russian practice. The study is based on domestic and foreign scientific sources of both legal and medical nature, as well as current and projected legal acts in the field of medical services, digital technologies, and personal data protection. Formal-legal, comparative-legal, statistical, and prognostic methods are used. Several problems that require a conceptual solution, including the issue of the safety of personal data and the issue of responsibility for a medical error resulting from the use of artificial intelligence technology or a technical device have been identified. Both are unlikely to be completely resolved at the current level of legal regulation and technological development. This, however, only confirms the need to introduce appropriate experimental regimes in order to use the accumulated empirical material to find solutions to existing and abstractly predictable problems.

Cov-Fed: Federated learning-based framework for COVID-19 diagnosis using chest X-ray scans

SARS-CoV-2, a member of the coronavirus family, causes COVID-19, which can range from the ordinary cold to the rare but fatal Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Disease (MERS). Radiologists can better diagnose COVID-19 using deep learning and computer vision techniques. However, training requires large centralized datasets. In addition, medical data protection prevents centralized server training with medical data. In this study, we propose a federated learning-based framework, Cov-Fed, to facilitate decentralized training of medical data. Cov-Fed is characterized by the proposed Multi-Efficient Channel Attention Network (MECAN) and a multi-model user-server weight update mechanism, respectively. In addition, Cov-Fed leverages PySyft encryption and decryption mechanisms for privacy preservation. Due to the salient nature of features corresponding to viruses, the classification of x-ray scans is challenging. Hence, we propose a multi-ECA attention mechanism embedded in the Cov-Fed to enhance feature maps of chest X-ray scans for classification without compromising performance. Extensive experiments are conducted on several public medical datasets and compared with some state-of-the-art models. Based on several evaluation metrics, Cov-Fed exhibited satisfactory performance with an average accuracy of 87.65%, an inference time of 92.8s, and ROC-AUC of 92.46% compared with some state-of-the-art models.

Medical Records and Personal Data Protection

Medical Records and Personal Data Protection

Retracted: Privacy Protection of Medical Service Data Based on Blockchain and Artificial Intelligence in the Era of Smart Medical Care

Retracted: Privacy Protection of Medical Service Data Based on Blockchain and Artificial Intelligence in the Era of Smart Medical Care

Merkle tree-blockchain-assisted privacy preservation of electronic medical records on offering medical data protection through hybrid heuristic algorithm

Merkle tree-blockchain-assisted privacy preservation of electronic medical records on offering medical data protection through hybrid heuristic algorithm

Secure Healthcare Website using Blockchain

Blockchain technology is consistently being an interested topic of research for researchers, and multiple of businesses as organizations are highly benefitted from its features. Blockchain technology has many benefits for the healthcare sector, including security, privacy, secrecy, and decentralisation. Privacy and protection of medical data are some of the important issues to looked after while availing any medical services. Secure storage is something which people look up for. Efficient Healthcare System is which allows the users to communicate securely without any worries about their data. This study is about how the blockchain technology can be applied to change the EHR systems and potentially provide a fix for these problems. A framework integrating EHR and blockchain to enable a secure medical data transfer between patients and hospitals is the objective of this study.

Protection of COVID-19 images using multiple elliptic curve cryptography

ABSTRACT COVID-19 pandemic has made the medical industry around the world under unprecedented and growing pressure. To preserve the integrity and protection of medical data for transmission and for secure diagnosis, this work suggests an encryption method for the protection of privacy of COVID-19 patient’s data by securing medical images based on elliptic curve cryptography. This is done through amalgamating three different types of stages by using elliptic curve cryptography. First, the coordinates of pixels of medical images are scrambled using elliptic curve and encrypt the coordinates of pixels, which help in decreasing the correlation between the image’s pixels. The second stage empowers the first stage by encrypting the group of pixels from previous outputs irrespective whether the pixel value lies on the curve or not based on the multiplication modulo operation of elliptic curve cryptography. Finally, the group of pixels from the previous output is encrypted by XORing with the key generated from ECC DHKE (Elliptic Curve Cryptography Diffie–Hellman Key Exchange). The NIST test suite examines and verifies the statistical characteristics of the binary sequences for 2 10 bits and 2 16 bits that are created by cryptographic random or pseudorandom number generators. The outcomes of the experiments indicate how the suggested approach satisfies the security requirements of COVID-19 images of patients in terms of high effectiveness in encryption quality, resilient against many statistical analyses and attacks and also performs better than some recent schemes. This work also evaluated comparisons of quantitative, differential, time consumptions and computational complexity with several recent schemes.

Risk and UCON-based access control model for healthcare big data

The rapid development of healthcare big data has brought certain convenience to medical research and health management, but privacy protection of healthcare big data is an issue that must be considered in the process of data application. Access control is one of the methods for privacy protection, but traditional access control models cannot adapt to the dynamic, continuous, and real-time characteristics of healthcare big data scenarios. In this paper, we propose an access control model based on risk quantification and usage control (RQ-UCON). The model adds a risk quantification module to the traditional UCON model to achieve privacy protection of medical data. This module classifies risks into direct and indirect risks and quantifies them based on the physician's visit history. The model stores the quantified risk values as subject attributes. The RQ-UCON model uses an improved Exponentially Weighted Moving Average (EWMA) and penalty factors to predict risk value and to update the risk values of the subject attributes in real-time. The RQ-UCON model uses agglomerative hierarchical clustering to cluster the risk values of physicians within the department, resulting in risk intervals for each physician's operational behavior. Each risk interval is stored as a condition in the RQ-UCON model. Finally, according to the model whether the subject attributes meet the model conditions to determine whether the subject has the corresponding access rights, and according to the risk interval to grant the subject the corresponding access rights. Through the final experiment, it can be seen that the access control model proposed in this paper has a certain control on the excessive access behavior of doctors and has a certain limitation on the privacy leakage of healthcare big data.

PHYSICIAN SCIENTIST: CLASH OF PATIENT RIGHTS AND PRINCIPLES OF CONDUCTING RESEARCH

Conducting scientific research, learning about the etiology of diseases, and searching for new methods of treatment are undoubtedly the basis of medicine. For centuries, a doctor has been a person who not only treated people, but also conducted scientific research aimed at deepening the knowledge about man. Due to the development of genetics, the pharmaceutical industry, and biobanks, this research has become mass and sometimes it is only human biological samples that are sufficient to carry it out. All this, undoubtedly, enables faster development of science, but puts a doctor in an extremely difficult situation of playing two roles, i.e. treating the patient and conducting scientific research using one’s biological material. In medical law, it has been emphasized for years that the basis of the relationship between a doctor and a patient is a special type of trust, which is systemically protected both by national and international legislature. The doctor is, therefore, obliged to act for the benefit of the patient. There is no doubt, however, that when conducting scientific research, a doctor sometimes faces the rivalry of patient rights, including the right to privacy and the right to freedom to conduct research. Both European and national lawmakers seem to notice these problems only partially, and only partially regulate the issue in question in both medical and personal data protection law. The subject of the reported research was analysis of the European and Polish law in terms of determining the extent to which this conflict of interests affects the patient’s rights and the doctor’s duties. In addition, the subject of analysis was to determine whether the person who gave a biological sample to the doctor to conduct research on it is always a patient and what consequences for the doctor’s legal liability this research on human biological samples has.

A New 3-Bit Hiding Covert Channel Algorithm for Public Data and Medical Data Security Using Format-Based Text Steganography

The primary concern of every individual and organization is the security of sensitive information generated via authorized activities; nonetheless, illicit data drawing and extraction by attackers is prevalent, which may be mitigated by covert approaches. Although cypher techniques give excellent protection, they raise suspicion in the eyes of adversaries, resulting in both passive and active assaults on the information sent. Steganography, on the other hand, helps to reduce third-party suspicion. This method conceals sensitive information on cover data and transports it to the targets without skepticism. However, the issue depends entirely on the effectiveness of the embedding method; it must also satisfy other data concealing features such as embedding capacity. As payload grows, so does skepticism. This article handled this issue to lessen suspicion while maintaining embedding capacity. The article proposes a format-based text concealing algorithm, a traditional way for dealing with embedding capacity and invisibility. The authors compared our results to those of other similar current methods. They discovered that theirs are pretty decent—the present study offered both standard public communication security and medical data protection.

Protection of Medical Record Data as a Form of Legal Protection of Health Data through the Personal Data Protection Act

This study aimed at analyzing government’s efforts to provide protection for medical record data of patients as a form of legal protection for patient’s medical data. In the midst of the flurry cases of personal data leakage by hackers, it has raised concerns from various parties about the possibility of medical records leaking of someone’s medical history. Medical history or medical record contains confidential information about a person’s condition related to health and the history of health care that has been carried out. It becomes particularly serious when it records certain diseases of the patient that should not be spread out to the public. In Indonesia, several regulations regarding the protection of personal data which is a person’s privacy rights have been formed. However, this is not enough to deal with the development of digital technology to provide legal certainty for the protection of personal data including medical records as one of the objectives of the law, namely to provide legal certainty and protection. Therefore, this study examines how the legal protection of medical record data based on legal protection according to positive law and the Personal Data Protection Act.

Review on Privacy Protection of Electronic Medical Data in Cross-domain Sharing

With the rapid development of information technology, the medical industry is rapidly moving in the direction of smart medical care, and more and more users tend to put their medical data in cloud servers, so as to share them safely among Internet hospitals. Electronic medical data stores all patients' medical information, and its high value is obvious to all, which also leads to the attack of illegal elements, which leads to the leakage of patients' private data. In addition, the cloud server used to store data is semi-trusted, so it is necessary for the intelligent development of the medical industry to ensure that the private data is not leaked when the electronic medical data is shared among internet hospitals. This paper deeply discusses different technical schemes to protect medical data, and then realizes the privacy protection of electronic medical data.

Blockchain-Based Medical Decision Support System

An urgent task at this moment is the use of blockchain technology to ensure the security of medical decision support systems (MDSS). Our research is devoted to development of blockchain-based MDSS (regarding possibility or impossibility of organ and tissue donation/transplantation, regarding possibility or impossibility of using reproductive technologies in the treatment of infertility). The developed blockchain-based medical decision support system provides reliable protection and security of medical information through the use of blockchain technology, provides support of decision regarding possibility or impossibility of organ and tissue donation/transplantation, provides support of decision regarding possibility or impossibility of use of reproductive technologies in the infertility treatment. The proposed blockchain-based medical decision support system: automates medical decision-making processes, minimizes the human factor and its influence on the medical decision process, and takes into account the norms of current legislation when making medical decisions, thereby allowing not to pay for the services of a hired lawyer, and also works with verified and protected medical data entered in the blockchain, which allows you to get rid of leaks of medical information and to ensure reliable protection of medical data.

Software system of automatic identification and distributed storage of patient medical data

Due to the rapid development of information technologies, informatization in the medical industry is essential. The main component of electronic health care is medical information systems designed for the accumulation, processing, analysis and transmis-sion of medical data. In the medical field, specialized software products are used to per-form diagnostic studies, process the results of laboratory tests, and make decisions at the stage of establishing a diagnosis. The use of mobile devices in medical information systems is developing. However, the degree of automation of processes in the provision of medical services and the protection of the personal and medical data of patients is still insufficient. The purpose of the research is to create a basic architecture of a software system that would simplify the process of developing software for automated input, processing, search and confidential patient access to their medical data in a medical information system based on multi-color barcoding of information using mobile devices. The architecture of the software system is proposed, in which, based on the princi-ples of distribution, anonymization, and data ownership, a patient can provide access to medical personnel to their medical data by reading a multi-color interference-resistant barcode from one smartphone (patient’s) by the camera of another smartphone (doctor’s). It is shown that in order to ensure the reliability of such transmission, it is neces-sary to use an interference-resistant barcode, which would ensure the integrity of the data in the conditions of possible distortion of the barcode image (change in lighting, scanning angle, trembling of the operator's hand, blurring or skewing of the image, etc.). The use of mobile devices for the barcode method of transmission and processing of data allows providing the protected electronic co-operating of a patient and a doctor both directly and remotely. It guarantees high reliability and confidentiality of the ex-change of data. The proposed technical solutions make it possible to improve the quality of medi-cal care and strengthen the protection of the patient's medical data.

Advances in medical image watermarking: a state of the art review.

Watermarking has been considered to be a potent and persuasive gizmo for its application in healthcare setups that work online, especially in the current COVID-19 scenario. The security and protection of medical image data from various manipulations that take place over the internet is a topic of concern that needs to be addressed. A detailed review of security and privacy protection using watermarking has been presented in this paper. Watermarking of medical images helps in the protection of image content, authentication of Electronic Patient Record (EPR), and integrity verification. At first, we discuss the various prerequisites of medical image watermarking systems, followed by the classification of Medical Image Watermarking Techniques (MIWT) that include state-of-the-art. We have classified MIWT's into four broader classes for providing better understanding of medical image watermarking. The existing schemes have been presented along with their cons so that the reader may be able to grasp the shortcomings of the technique in order to develop novel techniques proving the inevitability of the presented review. Further, various evaluation parameters along with potential challenges pertaining to medical image watermarking systems have been discussed to provide a deep insight into this research area.

Medical Record Digitization Policy: Overview of the Health Minister Regulation Number 24 of 2022

Objective: This study aims to examine the Regulation of the Minister of Health Number 24 of 2022 concerning Medical Records, which regulates electronic medical records.
 Methods: This research is juridical research with a statutory approach. Thus, this study only analyzes the rules and regulations related to legal or policy issues related to the digitization of medical records.
 Results: The obligation of the Electronic Medical Record (EMR) in Indonesia has legal certainty with the ratification of the Regulation of the Minister of Health of the Republic of Indonesia Number 24 of 2022 concerning Medical Records. This obligation has administrative consequences in the form of a written warning and/or recommendations for revocation or revocation of accreditation status for Health Service Facilities that commit violations. The provisions of this policy must go into effect no later than December 31, 2023.
 Conclusion: Three new things are regulated in the Regulation of the Minister of Health of the Republic of Indonesia Number 24 of 2022: the electronic system of electronic medical records, activities for organizing electronic medical records, security, and protection of electronic medical record data.

Privacy Protection of Medical Data Based on Multi-Scroll Memristive Hopfield Neural Network

Memristive Hopfield neural network (MHNN) has complex dynamic behavior, which is suitable for encryption applications. In order to ensure the information security of the medical data transmitted in Internet of Things (IoT), we propose three new MHNN models by using a non-ideal flux-controlled memristor model with multi-piecewise nonlinearity. In these models, there are complex dynamical behaviors such as coexisting attractors, multi-scroll attractors and grid multi-scroll attractors. In terms of hardware, the proposed model is implemented using field programmable gate array (FPGA). In addition, we provide a complete set of medical data sharing solution, which are helpful for the referral patients to receive timely medical treatment. The whole solution is successfully verified on Raspberry Pi, the encrypted Computed Tomography (CT) image is transmitted safely under Message Queuing Telemetry Transport (MQTT) protocol, and the CT image is subjected to basic security analysis. The results show that the ciphertext histogram is evenly distributed, the correlation between adjacent pixels is almost 0, the information entropy reaches 7.9977, and the values of number of pixels change rate (NPCR) and unified average change intensity (UACI) are 99.6078% and 33.4875%. The solution not only performs the exchange of medical data, but also protects the privacy of patients.

Protection of Health Data in Accordance with the GDPR: Selected Issues

Patients’ rights are widely commented issue in the medical and legal press. Attempts are being made to analyse issues relating to patient consent, the right to information about the medical procedures performed and the state of health, or the authority of medical personnel to make decisions about the patient’s person and the related procedures or treatments. This results in an increase in the importance of information, which has become one of the most important values in today’s world. Access to information, especially about oneself, means a certain social and legal awareness. Restrictions on access to information deprive people of the right to selfdetermination and, at the same time, the right to satisfy one of their needs, which is particularly important in today's world. Nowadays, it is unavoidable to process the data of any person, which is essential for the proper functioning of society, but above all for the benefit of each individual. This testifies that an individual is present in social, economic or political life. For over a year now, institutions providing medical services have been obliged to implement a number of regulations contained in the Regulation of the Parliament and Council 2016/679 of 27 April 2016 on the protection of individuals with regard to the processing of personal data and on the free movement of such data and repealing Directive 95/46/EC. Personal data relating to health are defined in the preamble of the Act. This Regulation does not indicate the organisational or technical measures to be taken by the data administrator to ensure data protection. These measures should be appropriate to the scope, purpose and risks of the data being processed. Sensitive data shall fall within the category of data for which processing involves the adoption of enhanced security measures. The task of the 99 data administrator is to introduce appropriate guarantees to ensure the implementation of appropriate technical and organizational measures so that the data processing meets the requirements of the GDPR and protects the rights of data subjects. Their task is also to adapt their forms, statements, e-mails or other queries so that they are clear, understandable and readable for the average recipient. For it is the quality that is the essence of information provided in the inquiry, not its number. The EU legislator has introduced several new developments to identify patterns of conduct and interpretations that are new concerning previous regulations. With the introduction of the GDPR, new procedures have been developed in order to exercise the rights of data subjects. However, the existing acquis of literature and judicature, as well as experience in the application of provisions ensuring the full entitlement of the data subjects, is not underestimated. More and more frequent analysis of the consequences of breaching the right to the protection of medical data and of the issue of giving and withdrawing consent to the processing of data may increase the importance of this right for society and thus ensure full protection of privacy and the information autonomy of the patient.

Improvement of Cloud Computing Medical Data Protection Technology Based on Symmetric Encryption Algorithm

Abstract The traditional data-protection method has the advantages of a long average secrecy time and low encryption efficiency in healthcare. This paper proposes an improved method of cloud-computing data-protection technology based on a symmetric encryption algorithm. According to the characteristics of cloud computing, a trusted communication channel for virtual machine monitoring is established on users and servers. The cloud-computing data-protection technology with four functional modules of “multi-copy protection,” “file access,” “integrity verification,” and “accountability” is deployed in the channel by using the improved symmetrical encryption differential-algebraic equations algorithm combined with the symmetrical encryption algorithms data encryption standard and advanced encryption standard to do the following: bind the identity of cloud-service providers; realize mixed encryption of plaintext segmentation; and add random interference information. These clusters are built on Hadoop to simulate the cloud-computing environment. The experimental results show that the average encryption and decryption times of this method are the best under different data amounts. At the same time, the encryption efficiency and throughput are over 95 %. The protection effect of this method on cloud-computing data is verified.

Medical Data, Reconciling Research and Data Protection

Most of our medical records are being processed electronically, centralised and easily accessible. In this paper, we will discuss the advantages of the system for research, as well as its potential challenges.