健康医疗可穿戴设备数据隐私相关问题研究

归纳、总结健康医疗可穿戴设备采集的数据内容,重点绘制健康医疗可穿戴设备的数据流动环节,并将数据流动划分为采集、上传、集成交互以及信息反馈等主要环节,并分析各主要环节中以及其他方面存在及潜在的数据安全与隐私问题,希望能为健康医疗可穿戴设备的数据隐私保护机制提供不同角度的理论参考。     

The Double Helix: Applying an Ethic of Care to the Duty to Warn Genetic Relatives of Genetic Information

Genetic testing reveals information about a patient's health status and predictions about the patient's future wellness, while also potentially disclosing health information relevant to other family members. With the increasing availability and affordability of genetic testing and the integration of genetics into mainstream medicine, the importance of clarifying the scope of confidentiality and the rules regarding disclosure of genetic findings to genetic relatives is prime. The United Nations International Declaration on Human Genetic Data urges an appreciation for principles of equality, justice, solidarity and responsibility in the context of genetic testing, including a commitment to honoring the privacy and security of the person tested. Considering this global mandate and recent professional statements in the context of a legal amendment to patient privacy policies in Australia, a fresh scrutiny of the legal history of a physician's duty to warn is warranted. This article inquiries whether there may be anything ethically or socially amiss with a potential future recommendation for health professionals or patients to universally disclose particular cancer predisposition genetic diagnosis to genetic family members. While much of the discussion remains applicable to all genetic diagnosis, the article focuses on the practice of disclosure within the context of BRCA1/2 diagnosis. An ‘ethic of care’ interpretation of legal tradition and current practice will serve to reconcile law and medical policy on the issue of physician disclosure of genetic results to family members without patient consent.     

Blockchain-based federated learning methodologies in smart environments

Blockchain technology is an undeniable ledger technology that stores transactions in high-security chains of blocks. Blockchain can solve security and privacy issues in a variety of domains. With the rapid development of smart environments and complicated contracts between users and intelligent devices, federated learning (FL) is a new paradigm to improve accuracy and precision factors of data mining by supporting information privacy and security. Much sensitive information such as patient health records, safety industrial information, and banking personal information in various domains of the Internet of Things (IoT) including smart city, smart healthcare, and smart industry should be collected and gathered to train and test with high potential privacy and secured manner. Using blockchain technology to the adaption of intelligent learning can influence maintaining and sustaining information security and privacy. Finally, blockchain-based FL mechanisms are very hot topics and cut of scientific edge in data science and artificial intelligence. This research proposes a systematic study on the discussion of privacy and security in the field of blockchain-based FL methodologies on the scientific databases to provide an objective road map of the status of this issue. According to the analytical results of this research, blockchain-based FL has been grown significantly during these 5 years and blockchain technology has been used more to solve problems related to patient healthcare records, image retrieval, cancer datasets, industrial equipment, and economical information in the field of IoT applications and smart environments.

     

Mutual authentication scheme of IoT devices in fog computing environment

The radical shift in the technology with the advent of connected things has led to the significant proliferation in demand for IoT devices, commonly called ‘smart devices’. These devices are capable of data collection, which can help in umpteen applications, particularly in healthcare. With the tremendous growth in these resource-constrained end devices, there has been a substantial increase in the number of attack varieties. Since these end devices deal with the sensitive data that might cause severe damage if not handled properly. Hence, defending its integrity, preserving its privacy, and maintaining its confidentiality as well as availability is of utmost importance. However, there are many protocols, models, architecture tools, etc. proposed to provide security. Nevertheless, almost every solution propound so far is not fully resilient and lacks in giving full protection to the system in some way or the other. So here, we have proposed a lightweight anonymous mutual authentication scheme for end devices and fog nodes.

     

Design and development of an intelligent transportation management system using blockchain and smart contracts

The automated toll-tax collection system (ATCS) is advantageous to facilitate traffic management at the toll plaza and to save fuel for vehicles. The most advanced application of the electronic toll collection (ETC) system is to collect the toll-tax amount (TA) at toll plazas of the national highways. The few existing TA collection systems suffer from data security, transparency, privacy, and data immutability as these are centralized systems. As the Blockchain is a decentralized, transparent, secure, and low-cost technology. However, this paper presents an intelligent transportation management system (I-TMS) using Blockchain. The proposed I-TMS shows the way of implementation of blockchain technology for vehicle data management in various applications of I-TMS. Herein, a framework of blockchain-enabled ATCS (BATCS) is provided as a blockchain-based I-TMS application to collect TAs without stopping vehicles while they pass the toll plaza. Smart contracts are used to authenticate vehicles’ data and to collect TAs automatically. An efficient algorithm is presented for data verification and TA collection in this paper. This research work provides a secure, transparent, and privacy-preserving framework in the field of the ETC system. The significant contributions of the BATCS compared with the RFID-based system are less fuel consumption and time-saving for a vehicle. The proposed framework can enhance data security and user privacy in the intelligent decentralized ETC system.

     

The Mining Minds digital health and wellness framework

Background

The provision of health and wellness care is undergoing an enormous transformation. A key element of this revolution consists in prioritizing prevention and proactivity based on the analysis of people’s conducts and the empowerment of individuals in their self-management. Digital technologies are unquestionably destined to be the main engine of this change, with an increasing number of domain-specific applications and devices commercialized every year; however, there is an apparent lack of frameworks capable of orchestrating and intelligently leveraging, all the data, information and knowledge generated through these systems.

Methods

This work presents Mining Minds, a novel framework that builds on the core ideas of the digital health and wellness paradigms to enable the provision of personalized support. Mining Minds embraces some of the most prominent digital technologies, ranging from Big Data and Cloud Computing to Wearables and Internet of Things, as well as modern concepts and methods, such as context-awareness, knowledge bases or analytics, to holistically and continuously investigate on people’s lifestyles and provide a variety of smart coaching and support services.

Results

This paper comprehensively describes the efficient and rational combination and interoperation of these technologies and methods through Mining Minds, while meeting the essential requirements posed by a framework for personalized health and wellness support. Moreover, this work presents a realization of the key architectural components of Mining Minds, as well as various exemplary user applications and expert tools to illustrate some of the potential services supported by the proposed framework.

Conclusions

Mining Minds constitutes an innovative holistic means to inspect human behavior and provide personalized health and wellness support. The principles behind this framework uncover new research ideas and may serve as a reference for similar initiatives.

     

SNUAGE: an efficient platform-as-a-service security framework for the cloud

In this paper we present SNUAGE, a platform-as-a-service security framework for building secure and scalable multi-layered services based on the cloud computing model. SNUAGE ensures the authenticity, integrity, and confidentiality of data communication over the network links by creating a set of security associations between the data-bound components on the presentation layer and their respective data sources on the data persistence layer. SNUAGE encapsulates the security procedures, policies, and mechanisms in these security associations at the service development stage to form a collection of isolated and protected security domains. The secure communication among the entities in one security domain is governed and controlled by a standalone security processor and policy attached to this domain. This results into: (1) a safer data delivery mechanism that prevents security vulnerabilities in one domain from spreading to the other domains and controls the inter-domain information flow to protect the privacy of network data, (2) a reusable security framework that can be employed in existing platform-as-a-service environments and across diverse cloud computing service models, and (3) an increase in productivity and delivery of reliable and secure cloud computing services supported by a transparent programming model that relieves application developers from the intricate details of security programming. Last but not least, SNUAGE contributes to a major enhancement in the energy consumption and performance of supported cloud services by providing a suitable execution container in its protected security domains for a wide suite of energy- and performance-efficient cryptographic constructs such as those adopted by policy-driven and content-based security protocols. An energy analysis of the system shows, via real energy measurements, major savings in energy consumption on the consumer devices as well as on the cloud servers. Moreover, a sample implementation of the presented security framework is developed using Java and deployed and tested in a real cloud computing infrastructure using the Google App Engine service platform. Performance benchmarks show that the proposed framework provides a significant throughput enhancement compared to traditional network security protocols such as the Secure Sockets Layer and the Transport Layer Security protocols.     

Redesigning healthcare: The 2.4 billion euro question?

Although it has been possible to transfer electrocardiograms via a phone line for more than 100 years, use of internet-based patient monitoring and communication systems in daily care is uncommon. Despite the introduction of numerous health-monitoring devices, and despite most patients having internet access, the implementation of individualised healthcare services is still limited. On the other hand, hospitals have invested heavily in massive information systems offering limited value for money and connectivity. However, the consumer market for personal healthcare devices is developing rapidly and with the current healthcare-related investments by tech companies it can be expected that the way healthcare is provided will change dramatically. Although a variety of initiatives under the banner of ‘e-Health’ are deployed, most are characterised by either industry-driven developments without proven clinical effectiveness or individual initiatives lacking the embedding within the traditional organisations. However, the introduction of numerous smart devices and internet-based technologies facilitates the fundamental redesign of healthcare based on the principle of achieving the best possible care for the individual patient at the lowest possible cost. Conclusion The way healthcare is delivered will change, but to what degree healthcare professionals together with patients will be able to redesign healthcare in a structured manner is still a question.     

An Improved Method with High Anti-interference Ability for R Peak Detection in Wearable Devices

The rapid development of the wearable electrocardiogram monitoring equipment increases the requirements for R peak detection in wearable devices. An improved method called ISC algorithm is proposed with high anti-interference ability for R peak detection in wearable devices based on a simple basic algorithm called SC algorithm. The proposed method is characterized by using the updated amplitude selection threshold, updated slope comparison threshold and RR interval judgement to reduce false positives and false negatives. For data from MIT-BIH Arrhythmia Database, the positive predictivity P+ of ISC algorithm can reach 99.12%, and the sensitivity Se of ISC algorithm is more than 95%. For MIT-BIH Noise Stress Test Database, the accuracy of ISC algorithm for both sensitivity Se and positive predictivity P+ can exceed 94% under three common noise, baseline wander, muscle artifact, and electrode motion artifact, where the positive predictivity P+ of ISC algorithm is 44.46% higher than that of SC algorithm on average. For wearable devices in exercise, even under the exercise intensity of 7 km per hour, the average positive predictivity P+ of ISC algorithm is 99.32%, which is 60.93% higher than that of SC algorithm. The high anti-interference ability shows that ISC algorithm is suitable for R peak detection in wearable devices.     

Security and privacy qualities of medical devices: an analysis of FDA postmarket surveillance

Background

Medical devices increasingly depend on computing functions such as wireless communication and Internet connectivity for software-based control of therapies and network-based transmission of patients’ stored medical information. These computing capabilities introduce security and privacy risks, yet little is known about the prevalence of such risks within the clinical setting.

Methods

We used three comprehensive, publicly available databases maintained by the Food and Drug Administration (FDA) to evaluate recalls and adverse events related to security and privacy risks of medical devices.

Results

Review of weekly enforcement reports identified 1,845 recalls; 605 (32.8%) of these included computers, 35 (1.9%) stored patient data, and 31 (1.7%) were capable of wireless communication. Searches of databases specific to recalls and adverse events identified only one event with a specific connection to security or privacy. Software-related recalls were relatively common, and most (81.8%) mentioned the possibility of upgrades, though only half of these provided specific instructions for the update mechanism.

Conclusions

Our review of recalls and adverse events from federal government databases reveals sharp inconsistencies with databases at individual providers with respect to security and privacy risks. Recalls related to software may increase security risks because of unprotected update and correction mechanisms. To detect signals of security and privacy problems that adversely affect public health, federal postmarket surveillance strategies should rethink how to effectively and efficiently collect data on security and privacy problems in devices that increasingly depend on computing systems susceptible to malware.     

Will You Accept the Government's Friend Request? Social Networks and Privacy Concerns

Participating in social network websites entails voluntarily sharing private information, and the explosive growth of social network websites over the last decade suggests shifting views on privacy. Concurrently, new anti-terrorism laws, such as the USA Patriot Act, ask citizens to surrender substantial claim to privacy in the name of greater security. I address two important questions regarding individuals'' views on privacy raised by these trends. First, how does prompting individuals to consider security concerns affect their views on government actions that jeopardize privacy? Second, does the use of social network websites alter the effect of prompted security concerns? I posit that prompting individuals to consider security concerns does lead to an increased willingness to accept government actions that jeopardize privacy, but that frequent users of websites like Facebook are less likely to be swayed by prompted security concerns. An embedded survey experiment provides support for both parts of my claim.     

openPDS: Protecting the Privacy of Metadata through SafeAnswers

The rise of smartphones and web services made possible the large-scale collection of personal metadata. Information about individuals'' location, phone call logs, or web-searches, is collected and used intensively by organizations and big data researchers. Metadata has however yet to realize its full potential. Privacy and legal concerns, as well as the lack of technical solutions for personal metadata management is preventing metadata from being shared and reconciled under the control of the individual. This lack of access and control is furthermore fueling growing concerns, as it prevents individuals from understanding and managing the risks associated with the collection and use of their data. Our contribution is two-fold: (1) we describe openPDS, a personal metadata management framework that allows individuals to collect, store, and give fine-grained access to their metadata to third parties. It has been implemented in two field studies; (2) we introduce and analyze SafeAnswers, a new and practical way of protecting the privacy of metadata at an individual level. SafeAnswers turns a hard anonymization problem into a more tractable security one. It allows services to ask questions whose answers are calculated against the metadata instead of trying to anonymize individuals'' metadata. The dimensionality of the data shared with the services is reduced from high-dimensional metadata to low-dimensional answers that are less likely to be re-identifiable and to contain sensitive information. These answers can then be directly shared individually or in aggregate. openPDS and SafeAnswers provide a new way of dynamically protecting personal metadata, thereby supporting the creation of smart data-driven services and data science research.     

Intelligent security and privacy solutions for enabling personalized telepathology

Starting with the paradigm change of health systems towards personalized health services, the paper introduces the technical paradigms to be met for enabling ubiquitous pHealth including ePathology. The system-theoretical, architecture-centric approach to mobile, pervasive and autonomous solutions has to be based on an open component system framework such as the Generic Component Model. The crucial challenge to be met for comprehensive interoperability is multi-disciplinary knowledge representation, which must be integrated into the aforementioned framework. The approach is demonstrated for security and privacy services fundamental for any eHealth or ePathology environment.     

Textile‐Based Electrochemical Energy Storage Devices

In the past few years, insensitive attentions have been drawn to wearable and flexible energy storage devices/systems along with the emergence of wearable electronics. Much progress has been achieved in developing flexible electrochemical energy storage devices with high end‐use performance. However, challenges still remain in well balancing the electrochemical properties, mechanical properties, and the processing technologies. In this review, a specific perspective on the development of textile‐based electrochemical energy storage devices (TEESDs), in which textile components and technologies are utilized to enhance the energy storage ability and mechanical properties of wearable electronic devices, is provided. The discussion focuses on the material preparation and characteristics, electrode and device fabrication strategies, electrochemical performance and metrics, wearable compatibility, and fabrication scalability of TEESDs including textile‐based supercapacitors and lithium‐ion batteries.     

Addressing antimicrobial resistance by improving access and quality of care—A review of the literature from East Africa

Universal access to healthcare, including quality medicines, is a fundamental human right but is still out of reach for many in low- and middle-income countries (LMICs). An existing framework capturing variability of access to healthcare in low-resource settings includes the 5 dimensions: availability, accessibility, affordability, adequacy, and acceptability. This framework encompasses key components, including health infrastructure and means to access it as well as service organisation, costs, and factors that influence users’ satisfaction. However, in reality, the effectiveness of accessed healthcare is measured by the likelihood of a positive outcome. We therefore propose an expansion of this framework to include an additional dimension, “aspects of quality,” incorporating quality, which critically influences the ability of the accessed services to generate optimal health outcomes. Within this framework, we explore literature from East Africa likely relevant to a range of LMIC contexts, mainly focusing on the provision of widely used antimicrobials such as antimalarials and antibiotics. We argue that major inadequacies exist across all 6 dimensions of access and quality of drugs and their provision. While the global focus is on curbing excessive antimicrobial use to tackle the antimicrobial resistance (AMR) crisis, major constraints around access shape patients’ health-seeking decisions leading to potentially problematic practices that might exacerbate the AMR problem. We advocate for a holistic approach to tackling these inadequacies, encompassing all dimensions of access and quality of healthcare in order to improve health outcomes while simultaneously counteracting the AMR crisis.     

Switch-based biosensors: a new approach towards real-time, in vivo molecular detection

Although the ability to monitor specific molecules in vivo in real-time could revolutionize many aspects of healthcare, the technological challenges that stand in the way of reaching this goal are considerable and are poorly met by most existing analytical approaches. Nature, however, has already solved the problem of real-time molecular detection in complex media by employing biomolecular "switches". That is, protein and nucleic acids that sense chemical cues and, by undergoing specific, binding-induced conformational changes, transduce this recognition into high-gain signal outputs. Here, we argue that devices that employ such switches represent a promising route towards versatile, real-time molecular monitoring in vivo.     

SHARE-ABE: an efficient and secure data sharing framework based on ciphertext-policy attribute-based encryption and Fog computing

Attribute-based encryption (ABE) is an access control mechanism that ensures efficient data sharing among dynamic groups of users by setting up access structures indicating who can access what. However, ABE suffers from expensive computation and privacy issues in resource-constrained environments such as IoT devices. In this paper, we present SHARE-ABE, a novel collaborative approach for preserving privacy that is built on top of Ciphertext-Policy Attribute-Based Encryption (CP-ABE). Our approach uses Fog computing to outsource the most laborious decryption operations to Fog nodes. The latter collaborate to partially decrypt the data using an original and efficient chained architecture. Additionally, our approach preserves the privacy of the access policy by introducing false attributes. Furthermore, we introduce a new construction of a collaboration attribute that allows users within the same group to combine their attributes while satisfying the access policy. Experiments and analyses of the security properties demonstrate that the proposed scheme is secure and efficient especially for resource-constrained IoT devices.

     

Genomics and privacy: implications of the new reality of closed data for the field

Open source and open data have been driving forces in bioinformatics in the past. However, privacy concerns may soon change the landscape, limiting future access to important data sets, including personal genomics data. Here we survey this situation in some detail, describing, in particular, how the large scale of the data from personal genomic sequencing makes it especially hard to share data, exacerbating the privacy problem. We also go over various aspects of genomic privacy: first, there is basic identifiability of subjects having their genome sequenced. However, even for individuals who have consented to be identified, there is the prospect of very detailed future characterization of their genotype, which, unanticipated at the time of their consent, may be more personal and invasive than the release of their medical records. We go over various computational strategies for dealing with the issue of genomic privacy. One can "slice" and reformat datasets to allow them to be partially shared while securing the most private variants. This is particularly applicable to functional genomics information, which can be largely processed without variant information. For handling the most private data there are a number of legal and technological approaches-for example, modifying the informed consent procedure to acknowledge that privacy cannot be guaranteed, and/or employing a secure cloud computing environment. Cloud computing in particular may allow access to the data in a more controlled fashion than the current practice of downloading and computing on large datasets. Furthermore, it may be particularly advantageous for small labs, given that the burden of many privacy issues falls disproportionately on them in comparison to large corporations and genome centers. Finally, we discuss how education of future genetics researchers will be important, with curriculums emphasizing privacy and data security. However, teaching personal genomics with identifiable subjects in the university setting will, in turn, create additional privacy issues and social conundrums.     

Potential for industrial ecology to support healthcare sustainability: Scoping review of a fragmented literature and conceptual framework for future research

Healthcare is a critical service sector with a sizable environmental footprint from both direct activities and the indirect emissions of related products and infrastructure. As in all other sectors, the “inside‐out” environmental impacts of healthcare (e.g., from greenhouse gas emissions, smog‐forming emissions, and acidifying emissions) are harmful to public health. The environmental footprint of healthcare is subject to upward pressure from several factors, including the expansion of healthcare services in developing economies, global population growth, and aging demographics. These factors are compounded by the deployment of increasingly sophisticated medical procedures, equipment, and technologies that are energy‐ and resource‐intensive. From an “outside‐in” perspective, on the other hand, healthcare systems are increasingly susceptible to the effects of climate change, limited resource access, and other external influences. We conducted a comprehensive scoping review of the existing literature on environmental issues and other sustainability aspects in healthcare, based on a representative sample from over 1,700 articles published between 1987 and 2017. To guide our review of this fragmented literature, and to build a conceptual foundation for future research, we developed an industrial ecology framework for healthcare sustainability. Our framework conceptualizes the healthcare sector as comprising “foreground systems” of healthcare service delivery that are dependent on “background product systems.” By mapping the existing literature onto our framework, we highlight largely untapped opportunities for the industrial ecology community to use “top‐down” and “bottom‐up” approaches to build an evidence base for healthcare sustainability.     

Efficient chameleon hashing-based privacy-preserving auditing in cloud storage

Cloud storage is an important application service in cloud computing, it allows data users to store and access their files anytime, from anywhere and with any device. To ensure the security of the outsourced data, data user needs to periodically check data integrity. In some cases, the identity privacy of data user must be protected. However, in the existing preserving identity privacy protocols, data tag generation is mainly based on complex ring signature or group signature. It brings a heavy burden to data user. To ensure identity privacy of data user, in this paper we propose a novel identity privacy-preserving public auditing protocol by utilizing chameleon hash function. It can achieve the following properties: (1) the identity privacy of data user is preserved for cloud server; (2) the validity of the outsourced data is verified; (3) data privacy can be preserved for the auditor in auditing process; (4) computation cost to produce data tag is very low. Finally, we also show that our scheme is provably secure in the random oracle model, the security of the proposed scheme is related to the computational Diffie–Hellman problem and hash function problem.