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Sensors (Basel, Switzerland) Mar 2023Blockchain technology in the healthcare industry has potential to enable enhanced privacy, increased security, and an interoperable data record. Blockchain technology is... (Review)
Review
Blockchain technology in the healthcare industry has potential to enable enhanced privacy, increased security, and an interoperable data record. Blockchain technology is being implemented in dental care systems to store and share medical information, improve insurance claims, and provide innovative dental data ledgers. Because the healthcare sector is a large and ever-growing industry, the use of blockchain technology would have many benefits. To improve dental care delivery, researchers advocate using blockchain technology and smart contracts due to their numerous advantages. In this research, we concentrate on blockchain-based dental care systems. In particular, we examine the current research literature, pinpoint issues with existing dental care systems, and consider how blockchain technology may be used to address these issues. Finally, the limitations of the proposed blockchain-based dental care systems are discussed which may be regarded as open issues.
Topics: Blockchain; Technology; Privacy; Delivery of Health Care; Computer Security
PubMed: 36991986
DOI: 10.3390/s23063277 -
PloS One 2022The security of the tax system is directly related to the development of a country. The conventional process of tax payment laborious steps, so this process becomes a...
The security of the tax system is directly related to the development of a country. The conventional process of tax payment laborious steps, so this process becomes a cause of irregularities among taxpayers and tax authorities, increasing the rate of corruption in tax collection. Blockchain, as a distributed ledger technology, its unique advantages and promising applications in taxation offer an effective solution to the problems of electronic taxation. However, the transparency of blockchain exists the risk of privacy disclosure, the high degree of anonymity brings the problem of lack of user supervision. Therefore, for balancing the contradiction of taxpayer privacy and supervision, we propose a blockchain-based self-certified and anonymous e-taxing scheme, which uses blockchain as the underlying support, and utilizes cryptography technology such as self-certified public key, Diffie-Hellman, to reduce the taxpayer's reliance on the certificate authority, and protects the taxpayer's anonymity while realizing the tracking of the real identity of malicious taxpayers. The security analysis proves that the scheme has the properties such as anonymity, conditional privacy and unforgeability, etc. Finally, performance analysis shows that compared with similar schemes, the scheme significantly improves the registration efficiency, proving its practicability and implementability.
Topics: Blockchain; Privacy; Taxes; Technology
PubMed: 35789334
DOI: 10.1371/journal.pone.0270454 -
Pacific Symposium on Biocomputing.... 2023Scientists and policymakers alike have increasingly been interested in exploring ways to advance algorithmic fairness, recognizing not only the potential utility of...
Scientists and policymakers alike have increasingly been interested in exploring ways to advance algorithmic fairness, recognizing not only the potential utility of algorithms in biomedical and digital health contexts but also that the unique challenges that algorithms-in a datafied culture such as the United States-pose for civil rights (including, but not limited to, privacy and nondiscrimination). In addition to the technical complexities, separation of powers issues are making the task even more daunting for policymakers-issues that might seem obscure to many scientists and technologists. While administrative agencies (such as the Federal Trade Commission) and legislators have been working to advance algorithmic fairness (in large part through comprehensive data privacy reform), recent judicial activism by the Roberts Court threaten to undermine those efforts. Scientists need to understand these legal developments so they can take appropriate action when contributing to a biomedical data ecosystem and designing, deploying, and maintaining algorithms for digital health. Here I highlight some of the recent actions taken by policymakers. I then review three recent Supreme Court cases (and foreshadow a fourth case) that illustrate the radical power grab by the Roberts Court, explaining for scientists how these drastic shifts in law will frustrate governmental approaches to algorithmic fairness and necessitate increased reliance by scientists on self-governance strategies to promote responsible and ethical practices.
Topics: United States; Humans; Ecosystem; Computational Biology; Privacy
PubMed: 36541005
DOI: No ID Found -
The Medical Journal of Australia Jan 2023
Topics: Humans; Confidentiality; Privacy; Delivery of Health Care
PubMed: 36437589
DOI: 10.5694/mja2.51793 -
Behavior Research Methods Aug 2019Pervasive internet and sensor technologies promise to revolutionize psychological science. However, the data collected using these technologies are often very...
Pervasive internet and sensor technologies promise to revolutionize psychological science. However, the data collected using these technologies are often very personal-indeed, the value of the data is often directly related to how personal they are. At the same time, driven by the replication crisis, there is a sustained push to publish data to open repositories. These movements are in fundamental conflict. In this article, we propose a way to navigate this issue. We argue that there are significant advantages to be gained by ceding the ownership of data to the participants who generate the data. We then provide desiderata for a privacy-preserving platform. In particular, we suggest that researchers should use an interface to perform experiments and run analyses, rather than observing the stimuli themselves. We argue that this method not only improves privacy but will also encourage greater compliance with good research practices than is possible through open repositories.
Topics: Dissent and Disputes; Internet; Privacy; Publishing
PubMed: 31152387
DOI: 10.3758/s13428-019-01259-5 -
Cell Systems Feb 2022Genotype imputation is the inference of unknown genotypes using known population structure observed in large genomic datasets; it can further our understanding of...
Genotype imputation is the inference of unknown genotypes using known population structure observed in large genomic datasets; it can further our understanding of phenotype-genotype relationships and is useful for QTL mapping and GWASs. However, the compute-intensive nature of genotype imputation can overwhelm local servers for computation and storage. Hence, many researchers are moving toward using cloud services, raising privacy concerns. We address these concerns by developing an efficient, privacy-preserving algorithm called p-Impute. Our method uses homomorphic encryption, allowing calculations on ciphertext, thereby avoiding the decryption of private genotypes in the cloud. It is similar to k-nearest neighbor approaches, inferring missing genotypes in a genomic block based on the SNP genotypes of genetically related individuals in the same block. Our results demonstrate accuracy in agreement with the state-of-the-art plaintext solutions. Moreover, p-Impute is scalable to real-world applications as its memory and time requirements increase linearly with the increasing number of samples. p-Impute is freely available for download here: https://doi.org/10.5281/zenodo.5542001.
Topics: Cloud Computing; Computer Security; Genome-Wide Association Study; Genotype; Privacy
PubMed: 34758288
DOI: 10.1016/j.cels.2021.10.003 -
JAMA Network Open Apr 2024Hospital websites frequently use tracking technologies that transfer user information to third parties. It is not known whether hospital websites include privacy...
IMPORTANCE
Hospital websites frequently use tracking technologies that transfer user information to third parties. It is not known whether hospital websites include privacy policies that disclose relevant details regarding tracking.
OBJECTIVE
To determine whether hospital websites have accessible privacy policies and whether those policies contain key information related to third-party tracking.
DESIGN, SETTING, AND PARTICIPANTS
In this cross-sectional content analysis of website privacy policies of a nationally representative sample of nonfederal acute care hospitals, hospital websites were first measured to determine whether they included tracking technologies that transferred user information to third parties. Hospital website privacy policies were then identified using standardized searches. Policies were assessed for length and readability. Policy content was analyzed using a data abstraction form. Tracking measurement and privacy policy retrieval and analysis took place from November 2023 to January 2024. The prevalence of privacy policy characteristics was analyzed using standard descriptive statistics.
MAIN OUTCOMES AND MEASURES
The primary study outcome was the availability of a website privacy policy. Secondary outcomes were the length and readability of privacy policies and the inclusion of privacy policy content addressing user information collected by the website, potential uses of user information, third-party recipients of user information, and user rights regarding tracking and information collection.
RESULTS
Of 100 hospital websites, 96 (96.0%; 95% CI, 90.1%-98.9%) transferred user information to third parties. Privacy policies were found on 71 websites (71.0%; 95% CI, 61.6%-79.4%). Policies were a mean length of 2527 words (95% CI, 2058-2997 words) and were written at a mean grade level of 13.7 (95% CI, 13.4-14.1). Among 71 privacy policies, 69 (97.2%; 95% CI, 91.4%-99.5%) addressed types of user information automatically collected by the website, 70 (98.6%; 95% CI, 93.8%-99.9%) addressed how collected information would be used, 66 (93.0%; 95% CI, 85.3%-97.5%) addressed categories of third-party recipients of user information, and 40 (56.3%; 95% CI, 44.5%-67.7%) named specific third-party companies or services receiving user information.
CONCLUSIONS AND RELEVANCE
In this cross-sectional study of hospital website privacy policies, a substantial number of hospital websites did not present users with adequate information about the privacy implications of website use, either because they lacked a privacy policy or had a privacy policy that contained limited content about third-party recipients of user information.
Topics: Humans; Cross-Sectional Studies; Privacy; Hospitals; Information Dissemination; Policy
PubMed: 38602678
DOI: 10.1001/jamanetworkopen.2024.5861 -
PloS One 2023Information about individual behaviour is collected regularly by organisations. This information has value to businesses, the government and third parties. It is not...
Information about individual behaviour is collected regularly by organisations. This information has value to businesses, the government and third parties. It is not clear what value this personal data has to consumers themselves. Much of the modern economy is predicated on people sharing personal data, however if individuals value their privacy, they may choose to withhold this data unless the perceived benefits of sharing outweigh the perceived value of keeping the data private. One technique to assess how much individuals value their privacy is to ask them whether they might be willing to pay for an otherwise free service if paying allowed them to avoid sharing personal data. Our research extends previous work on factors affecting individuals' decisions about whether to share personal data. We take an experimental approach and focus on whether consumers place a positive value on protecting their data by examining their willingness to share personal data in a variety of data sharing environments. Using five evaluation techniques, we systematically investigate whether members of the public value keeping their personal data private. We show that the extent to which participants value protecting their information differs by data type, suggesting there is no simple function to assign a value for individual privacy. The majority of participants displayed remarkable consistency in their rankings of the importance of different types of data through a variety of elicitation procedures, a finding consistent with the existence of stable individual privacy preferences in protecting personal data. We discuss our findings in the context of research on the value of privacy and privacy preferences.
Topics: Humans; Privacy; Information Dissemination; Trust; Computer Security
PubMed: 37134067
DOI: 10.1371/journal.pone.0284581 -
Journal of Healthcare Engineering 2021With the close integration of science and technology and health, the broad application prospects of healthy interconnection bring revolutionary changes to health...
With the close integration of science and technology and health, the broad application prospects of healthy interconnection bring revolutionary changes to health services. Health and medical wearable devices can collect real-time data related to user health, such as user behavior, mood, and sleep, which have great commercial and social value. Healthcare wearable devices, as important network nodes for health interconnection, connect patients and hospitals with the Internet of Things and sensing technology to form a huge medical network. As wearable devices can also collect user data regardless of time and place, uploading data to the cloud can easily make the wearable device's system vulnerable to attacks and data leakage. Defects in technology can sometimes cause problems such as lack of control over data flow links in wearable devices, and data and privacy leaks are more likely to occur. In this regard, how to ensure the data security and user privacy while using healthcare wearable devices to collect data is a problem worth studying. This article investigates data from healthcare wearable devices, from technical, management, and legal aspects, and studies data security and privacy protection issues for healthcare wearable devices to protect data security and user privacy and promote the sustainable development of the healthcare wearable device industry and the scientific use of data collection.
Topics: Computer Security; Delivery of Health Care; Health Facilities; Humans; Privacy; Wearable Electronic Devices
PubMed: 33628404
DOI: 10.1155/2021/6656204 -
Medicine, Health Care, and Philosophy Jun 2023Developments in medical big data analytics may bring societal benefits but are also challenging privacy and other ethical values. At the same time, an overly restrictive...
Developments in medical big data analytics may bring societal benefits but are also challenging privacy and other ethical values. At the same time, an overly restrictive data protection regime can form a serious threat to valuable observational studies. Discussions about whether data privacy or data solidarity should be the foundational value of research policies, have remained unresolved. We add to this debate with an empirically informed ethical analysis. First, experiences with the implementation of the General Data Protection Regulation (GDPR) within a European research consortium demonstrate a gap between the aims of the regulation and its effects in practice. Namely, strictly formalised data protection requirements may cause routinisation among researchers instead of substantive ethical reflection, and may crowd out trust between actors in the health data research ecosystem; while harmonisation across Europe and data sharing between countries is hampered by different interpretations of the law, which partly stem from different views about ethical values. Then, building on these observations, we use theory to argue that the concept of trust provides an escape from the privacy-solidarity debate. Lastly, the paper details three aspects of trust that can help to create a responsible research environment and to mitigate the encountered challenges: trust as multi-agent concept; trust as a rational and democratic value; and trust as method for priority setting. Mutual cooperation in research-among researchers and with data subjects-is grounded in trust, which should be more explicitly recognised in the governance of health data research.
Topics: Humans; Europe; Privacy; Trust
PubMed: 36633724
DOI: 10.1007/s11019-022-10134-8