Existing approaches to protect the privacy of Electronic Health Records are either insufficient for existing medical laws or they are too restrictive in their usage. For example, smart card-based encryption systems require the patient to be always present to authorize access to medical records. Questionnaires were administered by 50 medical practitioners to identify and categorize different Electronic Health Records attributes. The system was implemented using multi biometrics of patients to access patient record in pre-hospital care.The software development tools employed were JAVA and MySQL database. The system provides applicable security when patients records are shared either with other practitioners, employers, organizations or research institutes. The result of the system evaluation shows that the average response time of 6 seconds and 11.1 seconds for fingerprint and iris respectively after ten different simulations. The system protects privacy and confidentiality by limiting the amount of data exposed to users.The system also enables emergency medical technicians to gain easy and reliable access to necessary attributes of patients Electronic Health Records while still maintaining the privacy and confidentiality of the data using the patients fingerprint and iris.
Advancements in healthcare industry with new technology and population growth has given rise to security threat to our most personal data. The healthcare data management system consists of records in different formats such as text, numeric, pictures and videos leading to data which is big and unstructured. Also, hospitals have several branches at different locations throughout a country and overseas. In view of these requirements a cloud based healthcare management system can be an effective solution for efficient health care data management. One of the major concerns of a cloud based healthca…
Pompeu Fabra University（庞培法布拉大学）；Universidad Autonoma de Madrid（马德里自治大学）；Universidad de Las Palmas de Gran Canaria（大加那利岛拉斯帕尔马斯大学）；Universidad del Atlántico Medio（中大西洋大学）；Polytechnique Montréal（蒙特利尔高等理工学院）
Background- This paper summarizes the state-of-the-art and applications based on online handwritting signals with special emphasis on e-security and e-health fields. Methods- In particular, we focus on the main achievements and challenges that should be addressed by the scientific community, providing a guide document for future research. Conclusions- Among all the points discussed in this article, we remark the importance of considering security, health, and metadata from a joint perspective. This is especially critical due to the double use possibilities of these behavioral signals.
Telecare medicine information systems (TMIS) present the platform to deliver clinical service door to door. The technological advances in mobile computing are enhancing the quality of healthcare and a user can access these services using its mobile device. Existing authentication schemes for TMIS are either vulnerable to attacks or they have higher computational cost. We propose a biometric based efficient authentication scheme for TMIS which only requires the computation of the hash and XOR functions.
As the Covid-19 pandemic grips the world, healthcare systems are being reshaped, where the e-health concepts become more likely to be accepted. Wearable devices often carry sensitive information from users which are exposed to security and privacy risks. Moreover, users have always had the concern of being counterfeited between the fabrication process and vendors' storage. Hence, not only securing personal data is becoming a crucial obligation, but also device verification is another challenge. To address biometrics authentication and physically unclonable functions (PUFs) need to be put in pl…
Charles Sturt University (CSU)（查尔斯特大学）；University of Western Sydney (UWS)（西悉尼大学）；Kent Institute Australia（澳大利亚肯特学院）；Asia Pacific International College (APIC)（亚太国际学院）；Australian Institute of Higher Education（澳大利亚高等教育学院）；AL Nisour University College（阿尔尼苏尔大学学院）；University of Kurdistan Hewler（库尔德斯坦赫勒大学）；AMA International University Bahrain (AMAIUB)（巴林AMA国际大学）
Health records data security is one of the main challenges in e-health systems. Authentication is one of the essential security services to support the stored data confidentiality, integrity, and availability. This research focuses on the secure storage of patient and medical records in the healthcare sector where data security and unauthorized access is an ongoing issue. A potential solution comes from biometrics, although their use may be time-consuming and can slow down data retrieval. This research aims to overcome these challenges and enhance data access control in the healthcare sector t…
As applications of biometric verification proliferate, users become more vulnerable to privacy infringement. Biometric data is very privacy sensitive as it may contain information as gender, ethnicity and health conditions which should not be shared with third parties during the verification process. Moreover, biometric data that has fallen into the wrong hands often leads to identity theft. Secure biometric verification schemes try to overcome such privacy threats. Unfortunately, existing secure solutions either introduce a heavy computational or communication overhead or have to accept a hig…
Electronic Health Records(EHR) are gaining a lot of popularity all over the world. The current EHR systems however have their fair share of problems related to privacy and security. We have proposed a mechanism which provides a solution to most of these problems. Using a permissioned Ethereum blockchain allows the hospitals and patients across the world to be connected to each other. Our mechanism uses a combination of symmetric and asymmetric key cryptography to ensure the secure storage and selective access of records. It gives patients full control over their health records and also allows …
Authentication plays a significant part in dealing with security in public and private sectors such as healthcare systems, banking system, transportation system and law and security. Biometric technology has grown quickly recently, especially in the areas of artificial intelligence and identity. Formerly, authentication process has depended on security measures like passcodes, identity fobs, and fingerprints. On the other hand, as just a consequence of these precautions, theft has increased in frequency. In response, biometric security was created, in which the identification of a person is ba…
Dodis et al. proposed an improved version of the fuzzy vault scheme, one of the most popular primitives used in biometric cryptosystems, requiring less storage and leaking less information. Recently, Blanton and Aliasgari have shown that the relation of two improved fuzzy vault records of the same individual may be determined by solving a system of non-linear equations. However, they conjectured that this is feasible for small parameters only. In this paper, we present a new attack against the improved fuzzy vault scheme based on the extended Euclidean algorithm that determines if two records …
An Electronic Health Record (EHR) system must enable efficient availability of meaningful, accurate and complete data to assist improved clinical administration through the development, implementation and optimisation of clinical pathways. Therefore data integrity is the driving force in EHR systems and is an essential aspect of service delivery at all levels. However, preserving data integrity in EHR systems has become a major problem because of its consequences in promoting high standards of patient care. In this paper, we review and address the impact of data integrity of the use of EHR sys…
Remote user authentication is critical requirement in Telecare Medicine Information System (TMIS) to protect the patient personal details, security and integrity of the critical medical records of the patient as the patient data is transmitted over insecure public communication channel called Internet. In 2013, Yan proposed a biometric based remote user authentication scheme and claimed that his scheme is secure. Recently, Dheerendra et al. demonstrated some drawbacks in Yan et al scheme and proposed an improved scheme to erase the drawbacks of Yan et al scheme. We analyze Dheerendra et al sch…
As a promising candidate to complement traditional biometric modalities, brain biometrics using electroencephalography (EEG) data has received a widespread attention in recent years. However, compared with existing biometrics such as fingerprints and face recognition, research on EEG biometrics is still in its infant stage. Most of the studies focus on either designing signal elicitation protocols from the perspective of neuroscience or developing feature extraction and classification algorithms from the viewpoint of machine learning. These studies have laid the ground for the feasibility of u…
My Health Record system is the Australian Government's digital health record system that holds My Health Record. My Health Record is a secure online health record containing consumers' health information. The system aims to provide health care professionals with access to key health information, e.g. listing medicines, allergies and key diagnoses; radiology and pathology test results. The system (previously named Personally Controlled Electronic Health Record) enables consumers to decide how to share information with any of their health care providers who are registered and connected to the sy…
Electronic Health Records (EHRs) have improved many aspects of healthcare and allowed for easier patient management for medical providers. Blockchains have been proposed as a promising solution for supporting Electronic Health Records (EHRs), but have also been linked to scalability concerns about supporting real-world healthcare systems. This paper quantifies the scalability issues and bottlenecks related to current blockchains and puts into perspective the limitations blockchains have with supporting healthcare systems. Particularly we show that well known blockchains such as Bitcoin, Ethere…
DNA fingerprinting is a cornerstone for human identification in forensics, where the sequence of highly polymorphic short tandem repeats (STRs) from an individual is compared against a DNA database. This presents significant privacy risks to individuals with DNA profiles in the database due to hacking by malicious attackers who may access the data and misuse it for secondary purposes. In this paper, we propose a novel cryptographic framework for jointly encrypting DNA-based fingerprints (STRs) with other biometric data, for example, facial images, such that the STRs and biometrics information …
Secure and privacy-preserving management of Personal Health Records (PHRs) has proved to be a major challenge in modern healthcare. Current solutions generally do not offer patients a choice in where the data is actually stored and also rely on at least one fully trusted element that patients must also trust with their data. In this work, we present the Health Access Broker (HAB), a patient-controlled service for secure PHR sharing that (a) does not impose a specific storage location (uniquely for a PHR system), and (b) does not assume any of its components to be fully secure against adversari…
We introduce an end-to-end private deep learning framework, applied to the task of predicting 30-day readmission from electronic health records. By using differential privacy during training and homomorphic encryption during inference, we demonstrate that our proposed pipeline could maintain high performance while providing robust privacy guarantees against information leak from data transmission or attacks against the model. We also explore several techniques to address the privacy-utility trade-off in deploying neural networks with privacy mechanisms, improving the accuracy of differentially…
XML Signature Wrapping (XSW) has been a relevant threat to web services for 15 years until today. Using the Personal Health Record (PHR), which is currently under development in Germany, we investigate a current SOAP-based web services system as a case study. In doing so, we highlight several deficiencies in defending against XSW. Using this real-world contemporary example as motivation, we introduce a guideline for more secure XML signature processing that provides practitioners with easier access to the effective countermeasures identified in the current state of research.
In e-healthcare record systems (EHRS), attribute-based encryption (ABE) appears as a natural way to achieve fine-grained access control on health records. Some proposals exploit key-policy ABE (KP-ABE) to protect privacy in such a way that all users are associated with specific access policies and only the ciphertexts matching the users' access policies can be decrypted. An issue with KP-ABE is that it requires an a priori formulation of access policies during key generation, which is not always practicable in EHRS because the policies to access health records are sometimes determined after ke…
The fuzzy commitment scheme is a cryptographic primitive that can be used to store biometric templates being encoded as fixed-length feature vectors protected. If multiple related records generated from the same biometric instance can be intercepted, their correspondence can be determined using the decodability attack. In 2011, Kelkboom et al. proposed to pass the feature vectors through a record-specific but public permutation process in order to prevent this attack. In this paper, it is shown that this countermeasure enables another attack also analyzed by Simoens et al. in 2009 which can ev…
The robust development of Electronic Health Records (EHRs) causes a significant growth in sharing EHRs for clinical research. However, such a sharing makes it difficult to protect patient's privacy. A number of automated de-identification tools have been developed to reduce the re-identification risk of published data, while preserving its statistical meaning. In this paper, we focus on the experimental evaluation of existing automated de-identification tools, as applied to our EHR database, to assess which tool performs better with each quasi-identifiers defined in our paper. Performance of e…
Facial recognition technologies are implemented in many areas, including but not limited to, citizen surveillance, crime control, activity monitoring, and facial expression evaluation. However, processing biometric information is a resource-intensive task that often involves third-party servers, which can be accessed by adversaries with malicious intent. Biometric information delivered to untrusted third-party servers in an uncontrolled manner can be considered a significant privacy leak (i.e. uncontrolled information release) as biometrics can be correlated with sensitive data such as healthc…
Due to patient privacy protection concerns, machine learning research in healthcare has been undeniably slower and limited than in other application domains. High-quality, realistic, synthetic electronic health records (EHRs) can be leveraged to accelerate methodological developments for research purposes while mitigating privacy concerns associated with data sharing. The current state-of-the-art model for synthetic EHR generation is generative adversarial networks, which are notoriously difficult to train and can suffer from mode collapse. Denoising Diffusion Probabilistic Models, a class of …
