scholarly journals Privacy-Preserving Pandemic Monitoring

2021 ◽  
pp. 194-206
Author(s):  
Thu Yein Win ◽  
Hugo Tianfield
Keyword(s):  
Public Health ◽  
Data Sharing ◽  
Data Privacy ◽  
Privacy Preserving ◽  
Patient Data ◽  
Future Research ◽  
Health Safety ◽  
Patient Data Privacy ◽  
Significant Challenge ◽  
The World

The recent COVID-19 pandemic has presented a significant challenge for health organisations around the world in providing treatment and ensuring public health safety. While this has highlighted the importance of data sharing amongst them, it has also highlighted the importance of ensuring patient data privacy in doing so. This chapter explores the different techniques which facilitate this, along with their overall implementations. It first provides an overview of pandemic monitoring and the privacy implications associated with it. It then explores the different privacy-preserving approaches that have been used in existing research. It also explores the strengths as well as their limitations, along with possible areas for future research.

scholarly journals Evaluation of Privacy Risks of Patients’ Data in China: Case Study

10.2196/13046 ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. e13046 ◽  
Author(s):  
Mengchun Gong ◽  
Shuang Wang ◽  
Lezi Wang ◽  
Chao Liu ◽  
Jianyang Wang ◽  
...  
Keyword(s):  
Health Care ◽  
Data Sharing ◽  
Data Privacy ◽  
Patient Data ◽  
Chinese Patients ◽  
Biomedical Data ◽  
Safe Harbor ◽  
Patient Privacy ◽  
Privacy Risk ◽  
Privacy Risks

Background Patient privacy is a ubiquitous problem around the world. Many existing studies have demonstrated the potential privacy risks associated with sharing of biomedical data. Owing to the increasing need for data sharing and analysis, health care data privacy is drawing more attention. However, to better protect biomedical data privacy, it is essential to assess the privacy risk in the first place. Objective In China, there is no clear regulation for health systems to deidentify data. It is also not known whether a mechanism such as the Health Insurance Portability and Accountability Act (HIPAA) safe harbor policy will achieve sufficient protection. This study aimed to conduct a pilot study using patient data from Chinese hospitals to understand and quantify the privacy risks of Chinese patients. Methods We used g-distinct analysis to evaluate the reidentification risks with regard to the HIPAA safe harbor approach when applied to Chinese patients’ data. More specifically, we estimated the risks based on the HIPAA safe harbor and limited dataset policies by assuming an attacker has background knowledge of the patient from the public domain. Results The experiments were conducted on 0.83 million patients (with data field of date of birth, gender, and surrogate ZIP codes generated based on home address) across 33 provincial-level administrative divisions in China. Under the Limited Dataset policy, 19.58% (163,262/833,235) of the population could be uniquely identifiable under the g-distinct metric (ie, 1-distinct). In contrast, the Safe Harbor policy is able to significantly reduce privacy risk, where only 0.072% (601/833,235) of individuals are uniquely identifiable, and the majority of the population is 3000 indistinguishable (ie the population is expected to share common attributes with 3000 or less people). Conclusions Through the experiments based on real-world patient data, this work illustrates that the results of g-distinct analysis about Chinese patient privacy risk are similar to those from a previous US study, in which data from different organizations/regions might be vulnerable to different reidentification risks under different policies. This work provides reference to Chinese health care entities for estimating patients’ privacy risk during data sharing, which laid the foundation of privacy risk study about Chinese patients’ data in the future.

The Courts, the Remote Hearing and the Pandemic: From Action to Reflection

2021 ◽  
Vol 44 (1) ◽  
Author(s):  
Michael Legg ◽  
Anthony Song
Keyword(s):  
Public Health ◽  
Rule Of Law ◽  
Empirical Data ◽  
Future Research ◽  
The Rule Of Law ◽  
The World ◽  
Data Gap

With the onset of the COVID-19 pandemic, courts around the world rapidly shifted to remote hearings. Balancing public health directives with the need to continue upholding the rule of law, what followed was the largest, unforeseen mass-pilot of remote hearings across the world. For courts this was necessarily a time of action, not reflection. However, after having maintained court operations, it is now necessary to reflect on the experience of remote courts and their users during an otherwise unprecedented situation. Unlike previous iterations of remote hearings, the COVID-19 experience was fully remote – whereby all participants took part in the hearing remotely. The difficulty is until now, almost no prior empirical data has existed on this type of fully remote hearing with the majority of previous research focused on the use of audiovisual links (‘AVLs’) to facilitate partially remote appearances within courtrooms. To bridge the research and data gap on fully remote hearings, this article draws on the previous body of literature to both examine the COVID-19 experience, and to assist in guiding future research and use of remote hearings.

scholarly journals Pediatric Mental and Behavioral Health in the Period of Quarantine and Social Distancing With COVID-19

10.2196/19867 ◽  
2020 ◽  
Vol 3 (2) ◽  
pp. e19867 ◽  
Author(s):  
Jiancheng Ye
Keyword(s):  
Public Health ◽  
Behavioral Health ◽  
Psychological Trauma ◽  
Mental Illnesses ◽  
Future Research ◽  
Clinical Practices ◽  
Social Distancing ◽  
Health Technologies ◽  
The World

The coronavirus disease (COVID-19) pandemic has spread rapidly throughout the world and has had a long-term impact. The pandemic has caused great harm to society and caused serious psychological trauma to many people. Children are a vulnerable group in this global public health emergency, as their nervous systems, endocrine systems, and hypothalamic-pituitary-adrenal axes are not well developed. Psychological crises often cause children to produce feelings of abandonment, despair, incapacity, and exhaustion, and even raise the risk of suicide. Children with mental illnesses are especially vulnerable during the quarantine and social distancing period. The inclusion of psychosocial support for children and their families are part of the health responses to disaster and disaster recovery. Based on the biopsychosocial model, some children may have catastrophic thoughts and be prone to experience despair, numbness, flashbacks, and other serious emotional and behavioral reactions. In severe cases, there may be symptoms of psychosis or posttraumatic stress disorder. Timely and appropriate protections are needed to prevent the occurrence of psychological and behavioral problems. The emerging digital applications and health services such as telehealth, social media, mobile health, and remote interactive online education are able to bridge the social distance and support mental and behavioral health for children. Based on the psychological development characteristics of children, this study also illustrates interventions on the psychological impact from the COVID-19 pandemic. Even though the world has been struggling to curb the influences of the pandemic, the quarantine and social distancing policies will have long-term impacts on children. Innovative digital solutions and informatics tools are needed more than ever to mitigate the negative consequences on children. Health care delivery and services should envision and implement innovative paradigms to meet broad well-being needs and child health as the quarantine and social distancing over a longer term becomes a new reality. Future research on children's mental and behavioral health should pay more attention to novel solutions that incorporate cutting edge interactive technologies and digital approaches, leveraging considerable advances in pervasive and ubiquitous computing, human-computer interaction, and health informatics among many others. Digital approaches, health technologies, and informatics are supposed to be designed and implemented to support public health surveillance and critical responses to children’s growth and development. For instance, human-computer interactions, augmented reality, and virtual reality could be incorporated to remote psychological supporting service for children’s health; mobile technologies could be used to monitor children’s mental and behavioral health while protecting their individual privacy; big data and artificial intelligence could be used to support decision making on whether children should go out for physical activities and whether schools should be reopened. Implications to clinical practices, psychological therapeutic practices, and future research directions to address current effort gaps are highlighted in this study.

scholarly journals On the Delta Plus Variant of SARS-CoV-2

2021 ◽  
Vol 3 (6) ◽  
pp. 52-55
Author(s):  
Selia Chowdhury ◽  
Mehedi Hasan Bappy
Keyword(s):  
Public Health ◽  
World Health Organization ◽  
Vaccine Efficacy ◽  
World Health ◽  
Future Research ◽  
Current Trends ◽  
The World ◽  
Associated Symptoms ◽  
Health Organization

The unprecedented consequences brought by the COVID pandemic are still going on, the virus hasn’t been tamed yet. It is evolving through mutations to consistently being a risk to public health. Recently, the Delta variant has been declared as the variant of concern by the World Health Organization (WHO). In this article, a subvariant of Delta known as Delta Plus has been presented to provide a relevant foundation for future research works. The evolution, pathogenesis, associated symptoms, suggested prevention and treatments, vaccine efficacy, and current trends of transmission of Delta Plus variant of SARS-CoV-2 are reviewed and discussed.

scholarly journals Applying Blockchain Technology to Address the Crisis of Trust During the COVID-19 Pandemic

10.2196/20477 ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. e20477 ◽  
Author(s):  
Anjum Khurshid
Keyword(s):  
Public Health ◽  
Data Privacy ◽  
Well Being ◽  
Governance Structure ◽  
Privacy Preserving ◽  
Trust Value ◽  
Blockchain Technology ◽  
Trust Networks ◽  
Technology Applications ◽  
Potential Applications

Background The widespread death and disruption caused by the COVID-19 pandemic has revealed deficiencies of existing institutions regarding the protection of human health and well-being. Both a lack of accurate and timely data and pervasive misinformation are causing increasing harm and growing tension between data privacy and public health concerns. Objective This aim of this paper is to describe how blockchain, with its distributed trust networks and cryptography-based security, can provide solutions to data-related trust problems. Methods Blockchain is being applied in innovative ways that are relevant to the current COVID-19 crisis. We describe examples of the challenges faced by existing technologies to track medical supplies and infected patients and how blockchain technology applications may help in these situations. Results This exploration of existing and potential applications of blockchain technology for medical care shows how the distributed governance structure and privacy-preserving features of blockchain can be used to create “trustless” systems that can help resolve the tension between maintaining privacy and addressing public health needs in the fight against COVID-19. Conclusions Blockchain relies on a distributed, robust, secure, privacy-preserving, and immutable record framework that can positively transform the nature of trust, value sharing, and transactions. A nationally coordinated effort to explore blockchain to address the deficiencies of existing systems and a partnership of academia, researchers, business, and industry are suggested to expedite the adoption of blockchain in health care.

scholarly journals A Novel Privacy-Preserving Scheme in IoT-Based Social Distancing Technologies

2021 ◽  
Author(s):  
Arwa Alrawais ◽  
Fatemah Alharbi ◽  
Moteeb Almoteri ◽  
Sara A Aljwair ◽  
Sara SAljwair
Keyword(s):  
Data Privacy ◽  
Personal Information ◽  
Fog Computing ◽  
Mortality Rates ◽  
Privacy Preserving ◽  
Third Party ◽  
Massive Data ◽  
Social Distancing ◽  
The World ◽  
Efficiency And Effectiveness

The COVID-19 pandemic has swapped the world, causing enormous cases, which led to high mortality rates across the globe. Internet of Things (IoT) based social distancing techniques and many current and emerging technologies have contributed to the fight against the spread of pandemics and reduce the number of positive cases. These technologies generate massive data, which will pose a significant threat to data owners’ privacy by revealing their lifestyle and personal information since that data is stored and managed by a third party like a cloud. This paper provides a new privacy-preserving scheme based on anonymization using an improved slicing technique and implying distributed fog computing. Our implementation shows that the proposed approach ensures data privacy against a third party intending to violate it for any purpose. Furthermore, our results illustrate our scheme’s efficiency and effectiveness.

A Survey on Privacy Preserving Dynamic Data Publishing

2021 ◽  
pp. 1635-1657
Author(s):  
Salheddine Kabou ◽  
Sidi mohamed Benslimane ◽  
Mhammed Mosteghanemi
Keyword(s):  
Data Privacy ◽  
Privacy Preservation ◽  
Personal Information ◽  
Privacy Preserving ◽  
Data Publishing ◽  
Future Research ◽  
Dynamic Data ◽  
Practical Applications ◽  
New Process ◽  
Future Research Directions

Many organizations, especially small and medium business (SMB) enterprises require the collection and sharing of data containing personal information. The privacy of this data must be preserved before outsourcing to the commercial public. Privacy preserving data publishing PPDP refers to the process of publishing useful information while preserving data privacy. A variety of approaches have been proposed to ensure privacy by applying traditional anonymization models which focused only on the single publication of datasets. In practical applications, data publishing is more complicated where the organizations publish multiple times for different recipients or after modifications to provide up-to-date data. Privacy preserving dynamic data publication PPDDP is a new process in privacy preservation which addresses the anonymization of the data for different purposes. In this survey, the author will systematically evaluate and summarize different studies to PPDDP, clarify the differences and requirements between the scenarios that can exist, and propose future research directions.

scholarly journals Towards Smart Healthcare: Patient Data Privacy and Security in Sensor-Cloud Infrastructure

2018 ◽  
Vol 2018 ◽  
pp. 1-23 ◽  
Author(s):  
Isma Masood ◽  
Yongli Wang ◽  
Ali Daud ◽  
Naif Radi Aljohani ◽  
Hassan Dawood
Keyword(s):  
Data Privacy ◽  
Research Area ◽  
Research Unit ◽  
Patient Data ◽  
Cloud Infrastructure ◽  
Privacy And Security ◽  
Patient Data Privacy ◽  
Smart Healthcare ◽  
Sensor Cloud ◽  
Theory Research

Nowadays, wireless body area networks (WBANs) systems have adopted cloud computing (CC) technology to overcome limitations such as power, storage, scalability, management, and computing. This amalgamation of WBANs systems and CC technology, as sensor-cloud infrastructure (S-CI), is aiding the healthcare domain through real-time monitoring of patients and the early diagnosis of diseases. Hence, the distributed environment of S-CI presents new threats to patient data privacy and security. In this paper, we review the techniques for patient data privacy and security in S-CI. Existing techniques are classified as multibiometric key generation, pairwise key establishment, hash function, attribute-based encryption, chaotic maps, hybrid encryption, Number Theory Research Unit, Tri-Mode Algorithm, Dynamic Probability Packet Marking, and Priority-Based Data Forwarding techniques, according to their application areas. Their pros and cons are presented in chronological order. We also provide our six-step generic framework for patient physiological parameters (PPPs) privacy and security in S-CI: (1) selecting the preliminaries; (2) selecting the system entities; (3) selecting the technique; (4) accessing PPPs; (5) analysing the security; and (6) estimating performance. Meanwhile, we identify and discuss PPPs utilized as datasets and provide the performance evolution of this research area. Finally, we conclude with the open challenges and future directions for this flourishing research area.

Study on distributed privacy preserving data mining

2014 ◽  
Vol 11 (2) ◽  
pp. 163-170
Author(s):  
Binli Wang ◽  
Yanguang Shen
Keyword(s):  
Data Mining ◽  
Data Privacy ◽  
Rapid Development ◽  
Privacy Preserving ◽  
Future Research ◽  
Distributed Data ◽  
Distributed Environment ◽  
Privacy Preserving Data Mining ◽  
Advantages And Disadvantages ◽  
Future Research Directions

Recently, with the rapid development of network, communications and computer technology, privacy preserving data mining (PPDM) has become an increasingly important research in the field of data mining. In distributed environment, how to protect data privacy while doing data mining jobs from a large number of distributed data is more far-researching. This paper describes current research of PPDM at home and abroad. Then it puts emphasis on classifying the typical uses and algorithms of PPDM in distributed environment, and summarizing their advantages and disadvantages. Furthermore, it points out the future research directions in the field.

What do you know about me? Digital privacy and online data sharing in the UK insurance sector

2019 ◽  
Vol 18 (2) ◽  
pp. 281-303 ◽  
Author(s):  
Ian R. Blakesley ◽  
Anca C. Yallop
Keyword(s):  
Data Sharing ◽  
Data Privacy ◽  
Small Sample ◽  
Consumer Perceptions ◽  
Future Research ◽  
Research Approach ◽  
Exploratory Research ◽  
Content Type ◽  
Insurance Sector ◽  
The Uk

Purpose In addition to data transforming the insurance sector from within, insurance consumers and their behaviour has transformed significantly over the past 20 years from traditional retail to, predominantly, online trading. Data are a fundamental part of how the sector operates, and the use of data in insurance is constantly evolving. This paper aims to explore consumer perceptions about digital privacy and their subsequent motivations to disclose personal data for insurance purposes. Design/methodology/approach The study uses an exploratory research approach based on in-depth interviews to generate metathemes to provide an understanding of consumer perceptions about digital privacy and data sharing in the insurance sector. Findings Consumers were extrinsically motivated to disclose data by financial reward and convenience; however, subsequent intrinsic motivations may be an influence on the initial motivations. Consumers perceived transactions as “fair” if they received the expected rewards, retained control of the data, and the data was not unilaterally used to their detriment. Concern for privacy was generally low, provided antecedent conditions were met. Research limitations/implications As the study uses an exploration for discovery approach, the main limitation of this study is its small sample. However, this research aimed to identify metathemes and issues that may be the focus of future research in this area and is, therefore, not proposing to suggest strong conclusions and definitive answers. Originality/value This paper presents the first empirical research to examine data privacy issues in the UK insurance context. It contributes to knowledge in the areas of motivation, applied ethics and online consumer behaviour in general.

Sign in / Sign up

Export Citation Format

Share Document