Anonymous Data Research Articles

Using Data Anonymization in big data analytics security and privacy

Big Data and Analytics mean an enormous and complex collection of very diverse information, which is processed with various technologies and methods to produce and deliver useful and valuable insights. Analytics is the science of using data, or information to extract useful and actionable insights, facts and knowledge from a collection of data it could be stated that Big Data Analytics is the best thing since every commercial data system ever built, although everybody with a more optimistic vision of technology would like to take note that there is a fine line where Everything Data crosses the boundary to something else, especially with regard to privacy and security of the world as we know it. Privacy and security are two distinct but closely related phenomena. Whereas privacy refers to the control over access to the individual, security refers to the stability or strength of controls designed to protect the individual’s privacy. There are many obvious considerations and obstacles when attempting to securely share data. During big data analytics, many invasive techniques such as data fusion, cross-correlation, and algorithm training are often conducted over shared data, which can lead to severe privacy leaks. This means that every enterprise, organization, and individual maintaining large data repositories are in danger of being breached. Our study teaches us that security, privacy, and ethical concerns in big data analytics do not exist in parallel to the business cycle, but must be wisely and ethically managed in coherence throughout all emerging processes of the big data and information systems.

Pharmacokinetic variability of everolimus and impact of concomitant antiseizure medications in patients with tuberous sclerosis complex: A retrospective study of therapeutic drug monitoring data in Denmark and Norway.

The mTOR-inhibitor everolimus is a precision drug with antiepileptogenic properties approved for treatment of epilepsy in persons with tuberous sclerosis complex (TSC) in combination with other antiseizure medications (ASMs). However, the pharmacokinetic variability of everolimus is scarcely described, and the available information on pharmacokinetic interactions is scarce. The purpose of this study was to investigate pharmacokinetic variability of everolimus in patients with TSC, and the impact of age, sex and comedication. In this retrospective observational study we used anonymized data from medical records of patients with TSC using everolimus in Norway and Denmark, 2012 to 2020. Long-term therapeutic drug monitoring (TDM) identified inter-patient and intra-patient variability. The study included 59 patients, (36 females (61%)), median age 22 (range 3-59 years). Polytherapy was used in 50 patients (85%). The most frequently used ASMs were lamotrigine (n = 21), valproate (n = 17), and levetiracetam (n = 13). Blood concentrations of everolimus were measured in all patients. Pharmacokinetic variability of everolimus between patients was extensive, as demonstrated by a 24-fold variability from minimum-maximum concentration/dose (C/D)-ratios. The coefficient of variation (CV) for intra-patient (n = 59) and inter-patient variability (n = 47, ≥3 measurements) was 40% and 43%, respectively. The C/D-ratio of everolimus was 50% lower in 13 patients (22%) using enzyme-inducing ASMs compared to the 30 patients who did not (0.7 vs 1.4 ng/mL mg, P < .05). Age and sex were not significantly associated with changes in C/D-ratios of everolimus. Long-term TDM identified extensive variability in concentrations over time for everolimus both within and between patients, where comedication with enzyme-inducing ASMs was an important contributing factor. The findings suggest a need for TDM in patients with TSC treated with everolimus.

Does COVID-19 Revamp Nurses’ Compassion? Post-Pandemic Approach in Qatar

Aim: This study aimed to identify self-compassion among staff nurses after the COVID-19 pandemic in Qatar. Design: Descriptive cross-sectional survey design. Methods: Anonymous data were collected through an online survey using Microsoft Forms from 300 nurses in 14 health facilities in Qatar. The organization had almost 10,000 nursing staff working in different facilities. Data were gathered using a structured online questionnaire and included socio-demographic information, and the Self-Compassion Scale—Short Form was used to collect the remaining data. Correlation, t-test, and ANOVA analyses were conducted. Results: Nurses in the study showed high self-compassion. Among the sub-domain ‘mindfulness’, they showed comparatively high scores (7.96 ± 1.55), and the lowest score was for ‘isolation’ (6.15 ± 1.99). The score for ‘self-kindness’ was 7.29 ± 1.55, that for ‘self-judgement’ was 6.79 ± 2.01, that for ‘common humility’ was 6.62 ± 1.47, and that for the sub-domain ‘over-identified’ was 6.47 ± 1.91. Mindfulness scores were high among the nurse leaders. Moreover, over-identified scores were high among the nurses who were currently working under COVID-19 at the time of data collection. Conclusions: Nurses faced many difficulties while working during the COVID-19 pandemic, including a heavy workload and tension. The current study’s findings add to our understanding of how COVID-19 affected the development of self-compassion. A rise in mindfulness, which aids nurses in managing stress at work and building resilience, further underscores an increase in nurses’ acceptance of the COVID-19 pandemic. The findings also highlight how crucial it is to encourage self-compassion in individuals and offer them emotional support at such times, especially when there is a significant risk factor for mental health, such as COVID-19.

Potential, Pitfalls, and Future Directions for Remote Monitoring of Chronic Respiratory Diseases: Multicenter Mixed Methods Study in Routine Cystic Fibrosis Care.

The current literature inadequately addresses the extent to which remote monitoring should be integrated into care models for chronic respiratory diseases (CRDs). This study examined a remote monitoring program (RMP) in cystic fibrosis (CF) by exploring experiences, future perspectives, and use behavior over 3 years, with the aim of developing future directions for remote monitoring in CRDs. This was a mixed methods, multicenter, observational study in 5 Dutch CF centers following a sequential explanatory design. Self-designed questionnaires using the technology acceptance model were sent out to people with CF who had a minimum of 12 months of experience with the RMP and local health care professionals (HCPs). Questionnaire outcomes were used to inform semistructured interviews with HCPs and people with CF. Qualitative findings were reported following the COREQ (Consolidated Criteria for Reporting Qualitative Research) checklist. Anonymous data on use frequency of all people with CF were analyzed. Between the second quarter of 2020 and the end of 2022, a total of 608 people with CF were enrolled in the program, and a total of 9418 lung function tests and 2631 symptom surveys were conducted. In total, 65% (24/37) of HCPs and 89% (72/81) of people with CF responded to the questionnaire, and 7 HCPs and 12 people with CF participated in semistructured interviews. Both people with CF and HCPs were positive about remote monitoring in CF care and found the RMP a good addition to daily care (people with CF: 44/72, 61%; HCPs: 21/24, 88%). Benefits ranged from supporting individual patients to reducing health care consumption. The most valued monitoring tool was home spirometry by both people with CF (66/72, 92%) and HCPs (22/24, 92%). Downsides included the potential to lose sight of patients and negative psychosocial effects, as 17% (12/72) of people with CF experienced some form of stress due to the RMP. A large majority of people with CF (59/72, 82%) and HCPs (22/24, 92%) wanted to keep using the RMP in future, with 79% (19/24) of HCPs and 75% (54/72) of people with CF looking forward to more replacement of in-person care with digital care during periods of well-being. Future perspectives for the RMP were centered on creating hybrid care models, personalizing remote care, and balancing individual benefits with monitoring burden. Remote monitoring has considerable potential in supporting people with CF and HCPs within the CF care model. We identified 4 practice-based future directions for remote monitoring in CF and CRD care. The strategies, ranging from patient driven to prediction driven, can help clinicians, researchers, and policy makers navigate the rapidly changing digital health field, integrate remote monitoring into local care models, and align remote care with patient and clinician needs.

Blockchain-based anonymous authentication and data aggregation for advanced metering infrastructure in smart grid

This paper proposes a blockchain-based scheme, focusing on anonymous identity authentication and data aggregation, for safer and more reliable bidirectional communication between the utility company and power consumers based on Advanced Metering Infrastructure (AMI). Firstly, to cope with the mutual identity authentication between resource-constrained Smart Meters, a lightweight anonymous authentication strategy is designed using Elliptic Curve Cryptography. Meanwhile, a reputation-based consensus protocol is developed to accomplish data aggregation in AMI by using decentralization and non-tampering features of the blockchain. During the communication, in each time slot, the proposed scheme only needs to select a trusted user randomly to undertake the mining node rather than to introduce a third-party in a centralized manner to summarize and record the user-side data into the blockchain. Such scheme can effectively prevent data tampering and also be effective to decrease the processing complexity. The AVISPA tool is adopted to formally evaluate its security. The simulation results show promising performance. The proposed scheme not only can guarantee secure communication but also effectively decrease the computational cost in AMI.

The implementation specifics of the right to be forgotten in the context of the decisions of the Court of Justice of the European Union and the European Court of Human Rights

The article is dedicated to the legal analysis of the case law of the CJEU and the ECtHR regarding the implementation of the right to be forgotten and the right to privacy. It is established that the development of digital technologies has enabled rapid information exchange and its almost indefinite storage in the digital environment. However, such widespread availability of data about individuals and the inability to update or supplement this information have posed new challenges to society in ensuring the protection of personal data and privacy. The right to be forgotten is one of the tools through which a person can delete truthful but outdated information about themselves on the Internet, provided that such information is not of public interest. It is proven that although the right to be forgotten has been implemented within the EU for over a decade, lawyers and human rights activists consider it the second most complex obligation of the General Data Protection Regulation to implement. It is argued that both the CJEU and the ECtHR often inadequately describe the factual circumstances of cases and disregard the confidentiality of the parties involved. Individuals who apply to the court for the deletion or anonymization of personal data on the Internet often receive the opposite effect due to the public and scientific community’s interest in such cases. It is argued that in order to maintain a reasonable balance between privacy and freedom of expression, court decisions should contain all factual circumstances of the case, but the personal data of the parties involved and other circumstances that may indicate the applicant should be anonymized. This will help avoid censorship, ensure the right to memory, and enable an understanding of the factual basis on which courts have developed their legal arguments. It is argued that since the materials of cases before the ECtHR and the CJEU are often transmitted to national courts of member states for quality protection of confidentiality, it is necessary for them to correctly anonymize the personal data of the parties involved in the case and information that could identify the applicant.

Understanding the Use of Mobility Data in Disasters: Exploratory Qualitative Study of COVID-19 User Feedback.

Human mobility data have been used as a potential novel data source to guide policies and response planning during the COVID-19 global pandemic. The COVID-19 Mobility Data Network (CMDN) facilitated the use of human mobility data around the world. Both researchers and policy makers assumed that mobility data would provide insights to help policy makers and response planners. However, evidence that human mobility data were operationally useful and provided added value for public health response planners remains largely unknown. This exploratory study focuses on advancing the understanding of the use of human mobility data during the early phase of the COVID-19 pandemic. The study explored how researchers and practitioners around the world used these data in response planning and policy making, focusing on processing data and human factors enabling or hindering use of the data. Our project was based on phenomenology and used an inductive approach to thematic analysis. Transcripts were open-coded to create the codebook that was then applied by 2 team members who blind-coded all transcripts. Consensus coding was used for coding discrepancies. Interviews were conducted with 45 individuals during the early period of the COVID-19 pandemic. Although some teams used mobility data for response planning, few were able to describe their uses in policy making, and there were no standardized ways that teams used mobility data. Mobility data played a larger role in providing situational awareness for government partners, helping to understand where people were moving in relation to the spread of COVID-19 variants and reactions to stay-at-home orders. Interviewees who felt they were more successful using mobility data often cited an individual who was able to answer general questions about mobility data; provide interactive feedback on results; and enable a 2-way communication exchange about data, meaning, value, and potential use. Human mobility data were used as a novel data source in the COVID-19 pandemic by a network of academic researchers and practitioners using privacy-preserving and anonymized mobility data. This study reflects the processes in analyzing and communicating human mobility data, as well as how these data were used in response planning and how the data were intended for use in policy making. The study reveals several valuable use cases. Ultimately, the role of a data translator was crucial in understanding the complexities of this novel data source. With this role, teams were able to adapt workflows, visualizations, and reports to align with end users and decision makers while communicating this information meaningfully to address the goals of responders and policy makers.

An Anonymous and Secure Data Transmission Mechanism With Trajectory Tracking for D2D Relay Communication in 3GPP 5G Networks

An Anonymous and Secure Data Transmission Mechanism With Trajectory Tracking for D2D Relay Communication in 3GPP 5G Networks

Blockchain-based anonymous (IOT) data integrity auditing scheme in cloud environments

Blockchain-based anonymous (IOT) data integrity auditing scheme in cloud environments

A Data Ingestion Procedure towards a Medical Images Repository.

This article aims to create a repository of 33,000 medical CT images and 33,000 diagnostic reports with international standards (HL7 HAPI FHIR, DICOM, SNOMED). This goal requires devising a data ingestion procedure that can be replicated by other provider institutions, guaranteeing data privacy by implementing a pseudo-anonymization algorithm at the source, and generating labels from annotations via NLP. Our approach involves hybrid on-premise/cloud deployment of PACS and FHIR services, including transfer services for anonymized data to populate the repository through a structured ingestion procedure. We used NLP over the diagnostic reports to generate annotations, which were then used to train ML algorithms for content-based similar exam recovery. We successfully implemented ALPACS and PROXIMITY 2.0, ingesting almost 19,000 thorax CT exams to date along with their corresponding reports.

Exploring the Viability of ChatGPT for Personal Data Anonymization in Government: A Comprehensive Analysis of Possibilities, Risks, and Ethical Implications

Exploring the Viability of ChatGPT for Personal Data Anonymization in Government: A Comprehensive Analysis of Possibilities, Risks, and Ethical Implications

Big data anonymization using Spark for enhanced privacy protection

This article introduces an advanced solution for anonymizing large-scale sensitive data, addressing the limitations of traditional approaches when applied to vast datasets. By leveraging the Spark distributed computing framework, we propose a method that parallelizes the data anonymization process, enhancing efficiency and scalability. Utilizing Spark's resilient distributed datasets (RDD), the approach integrates two primary operations, Map_RDD and ReduceByKey_RDD, to execute the anonymization tasks. Our comprehensive experimental evaluation demonstrates our solution's effectiveness and improved performance in preserving data privacy while balancing data utility and confidentiality. A significant contribution of our study is the development of a wide array of solutions for data owners, particularly notable for a 500 MB dataset at an anonymity level of K=100, where our methodology produces 832 unique solutions. This study also opens avenues for future research in applying different privacy models within the Spark ecosystem, such as l-diversity and t-closeness.

The Spider: a visual, multisystemic symptom impact questionnaire for people with hypermobility-related disorders—validation in adults

IntroductionHypermobility spectrum disorders (HSD) and hypermobile Ehlers-Danlos syndrome (hEDS) are often accompanied by varied and complex multisystemic comorbid symptoms/conditions. The Spider questionnaire was developed to evaluate the presence and impact of eight common multisystemic comorbidities. Thirty-one questions across eight symptom domains assess neuromusculoskeletal, pain, fatigue, cardiac dysautonomia, urogenital, gastrointestinal, anxiety, and depression symptoms. This study aimed to evaluate the Spider’s construct validity in adults.MethodA cross-sectional observational study was conducted over four stages. Three international patient charities aided recruitment of participants through social media and website advertisements. Adults aged 18 to 65 years, with and without HSD/hEDS, were invited to participate. Validated, frequently used comparator questionnaires were used to establish convergent validity of Spider symptom domains. A control group was recruited for known-group validity analysis. Participants answered each Spider domain and the corresponding comparator questionnaire via surveys hosted by REDCap. Anonymous data were analysed using SPSS. Convergent validity was assessed through Spearman’s correlational analysis and known-group validity through Mann–Whitney U analysis.ResultsA total of 11,151 participants were recruited across the four stages. Statistically significant, moderate-to-strong correlations were found between all Spider domains and their comparators (p < 0.001, r = 0.63 to 0.80). Known-group validity analysis showed statistically significant differences (p < 0.001) between the hypermobile and control groups in all eight domains.ConclusionsConvergent and known-group validity of the Spider was established with adults. These results suggest the Spider can measure the presence and impact of multisystemic comorbid symptoms/conditions in adults with HSD/hEDS, providing a tool which guides multidisciplinary management.Key Points• The Spider questionnaire is a novel tool assessing the presence and impact of the multisystemic comorbid symptoms/conditions associated with HSD/hEDS.• Convergent and known-group validity of the Spider questionnaire was established in adults aged 18 to 65.• This tool provides a quick and easy method to visualise the symptom profile of those with HSD/hEDS to guide symptom management.

Extensive Review of Security and Privacy Issues in Heterogeneous Networks

This paper studies advanced network security, privacy, and performance issues for Heterogeneous Networks (HetNets), which combine multiple types of cells to enhance wireless communication coverage and capacity. The coexistence of heterogeneous network elements inherently leads to considerable issues in terms of security, privacy, and performance. Previous research has primarily addressed security issues using common cryptographic techniques including data encryption with AES, secure key exchange with RSA, and handoff security with mutual authentication. Data anonymization methods and regulatory compliance have been used to address privacy concerns. Allocating resources and managing interference are some of the tactics that have been used in performance optimization. Although the current solutions offer a solid base, they frequently have issues with computational overhead, scalability, and continuous maintenance needs. Performance optimization solutions might not sufficiently handle dynamic network conditions, and privacy protections might not be sufficient to mitigate sophisticated data harvesting operations. This study evaluates existing HetNets solutions using a thorough evaluation and analytical technique. It assesses how well they handle issues with security, privacy, and performance, points out any shortcomings, and suggests areas for further investigation. Our analysis emphasizes the need for improved security mechanisms, including quantum-resistant cryptography, AI-driven threat detection, and technologies that improve privacy, such as differential privacy and homomorphic encryption. Innovative resource management and optimization strategies catered to HetNets' dynamic nature are needed to address performance issues. The necessity of developing new security, privacy, and performance solutions to guarantee the stability and dependability of HetNets is emphasized by this study. Stakeholders can promote the broad adoption and smooth integration of HetNet technology by tackling these obstacles. To sum up, this study offers a thorough analysis of the HetNets' architectural, security, privacy, and performance issues. It lists existing remedies, analyses their drawbacks, and suggests new lines of inquiry for future development to advance the area and improve HetNets' operational capabilities.

Severe acute hepatitis of unknown origin in children: Is it still amystery? What role does adenovirus play?

On March 31, 2022, severe acute hepatitis of unknown origin was first reported from the Royal Glasgow Children's Hospital in Scotland. According to the criteria by WHO-ECDC, a probable case of unknown acute hepatitis in children is defined as a subject under 16 years of age, who tested negative for viral hepatitis and transaminases >500 U/L, starting from the 1st of October 2021. WHO invites Member States to participate in the global effort to collect anonymized clinical data on probable cases of severe acute hepatitis of unknown aetiology. As of May 26, 2021, 650 cases were already registered on the platform worldwide, of whom at least 38 cases have required liver transplants. Several hypotheses such as previous SARS-CoV-2 infection or coinfection or infection with another virus were examined and a strong association was found between adenovirus (41F) and acute hepatitis of unknown aetiology cases. This review article summarizes the global epidemiological evidences on acute hepatitis of unknown origin in children, analysing their incidence and characteristics.

Semantic Tree Based PPDP Technique for Multiple Sensitive Attributes in Inter Cloud

Digital devices and information systems have made data privacy essential. The collected data contains sensitive attributes such as salary, marital status and health history that need to be protected. Such data is exchanged or published to a third party using cloud infrastructure to perform various analyses, conduct research, and make critical decisions. Unauthorized users of the published data may violate privacy, notwithstanding the benefits. Data anonymization is one of the technique for achieving data privacy. Existing techniques consider single sensitive attribute and data is anonymized using generalization or suppression approaches. On observation, it is found that these techniques are less efficient since the collected data contains multiple sensitive attributes when anonymized using the same approaches leads to higher information loss and residue records. In this paper, multiple sensitive attributes are considered and the dataset is anonymized by constructing a semantic hierarchical tree it is further partitioned using the anatomy approach. Later, the partitions are stored in interclouds to achieve better privacy protection. Experiments are conducted to observe and analyze the computational performance, residue records and diversity percentage. The results obtained prove that the proposed technique is efficient when compared to the existing ones.

Introducing the Mellorater-The Five Domains Model in a Welfare Monitoring App for Animal Guardians.

When monitoring an animal's welfare, it helps to have comprehensive and day-to-day information about the animal's life. The goal is to ensure that animal guardians (carers, keepers, and owners) use such information to act in the animals' best interests. This article introduces the Mellorater, an animal welfare monitoring app based on the 2020 Five Domains Model. This framework provides a means of capturing comprehensive information about the world in which individual animals exist. The Mellorater asks animal guardians to rate their agreement with 18 statements covering any focal animal's nutrition, environment, health, and behavioural interactions using a five-point Likert scale. No specialist training is required other than following straightforward instructions on using the app, which are provided. The Mellorater is not proposed as a validated welfare auditing tool because it relies on reflective self-reporting and, thus, is vulnerable to the user's subjectivity. If users' subjectivity is stable over time, then the longitudinal data may be considered useful proxies for trends in quality of life. That said, it has the potential to be used by trained auditors if scientifically validated, species-specific indicators are applied. The Mellorater collects anonymous data and has been approved for a study to explore how the use of such scales may differ among guardians of different species and in different contexts. In this paper, we conduct the following: (1) summarise the app's purposes; (2) clarify its capabilities and limitations; and (3) invite animal welfare scholars, veterinarians, health and welfare professionals, and animal guardians to use it.

Diseases of the cardiovascular and respiratory systems as the basis for obtaining a disability certificate among patients from Lublin in 2006-2021

Introduction. People with disabilities are individuals with full rights, who find themselves in a handicapped situation due to environmental, economic and social barriers that they cannot overcome in the same way as other people. About 15% of the global population live with disability. The number of patients suffering from cardiovascular diseases (CVD) and pulmonary diseases is increasing. Aim. The aim of the study was to find out if CVD and lung diseases were among the leading causes of issuing disability certificates in Lublin in 2006-2021. Material and methods. The data was obtained through a query at the Municipal Disability Adjudication Council in Lublin. We obtained anonymized data from years 2006-2021 referring to 16+ population. Results. In the years 2006-2021 Municipal Disability Adjudication Council in Lublin issued 76,581 disability certificates for persons over 16 years of age. Out of that number 15,648 (20%) certificates were issued due to CVD and pulmonary diseases. These were on the second position among causes of disability after musculoskeletal diseases. The certificate recipients were mainly men &gt; 60years of age with secondary or vocational education. In all age groups unemployed persons predominated. Conclusion. The cardiovascular and pulmonary diseases were the second common reason of issuing disability certificates to adults in Lublin in the years 2006-2021. Keywords: disability, cardiovascular diseases, lung diseases.

Unexcused Absences and Failures: Dissecting the Variability in Course Credit Policies and Freshman Course Failure

This policy analysis examines the implementation of A.C.A. 6-18-222, a statewide policy in Arkansas that addresses unexcused absences and the subsequent consequences for course credit among students. Utilizing anonymized student-level data from the 2020-21 and 2021-22 school years, which includes a total of 65,651 freshmen, the study investigates the variability in policy implementation across districts. It also examines the differing language used to dictate the consequences of exceeding unexcused absence thresholds. Our multivariate logistic regression models demonstrate that students eligible for Free and Reduced Lunch (FRL) are notably more likely to fail a course after surpassing their district's absence threshold. Moreover, the data reveal that upon reaching this threshold, students are significantly more likely to fail core courses as opposed to non-core courses. These findings illuminate the variations in local policy implementation and their impact on student academic outcomes, emphasizing the importance of uniform policy enforcement to ensure equitable educational opportunities.

Security and Privacy Challenges in Software as a Service (SaaS)

This document In the rapidly evolving landscape of cloud computing, Software as a Service (SaaS) has emerged as a dominant model for delivering software applications over the internet. However, this model introduces significant security and privacy challenges. This research paper delves into these issues, highlighting the unique risks associated with SaaS platforms. The study explores common vulnerabilities such as data breaches, unauthorized access, data loss, and identity theft, which are exacerbated by the centralized nature of SaaS solutions where data is stored on remote servers managed by service providers. To address these challenges, the paper underscores the importance of robust security measures, including encryption, access controls, and secure software development practices. Additionally, it emphasizes the necessity for SaaS providers to adopt advanced privacy protection techniques like data anonymization and differential privacy to meet user expectations and comply with stringent legal regulations such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA). Through a comprehensive review of literature and analysis of current SaaS security practices, the research identifies critical risks and provides strategic recommendations for enhancing security and privacy in SaaS environments. By integrating multiple layers of security throughout the software development lifecycle, enforcing strict access management protocols, and ensuring compliance with regulatory standards, SaaS providers can significantly mitigate risks and safeguard sensitive user data. The findings of this study highlight the imperative for continuous improvement in SaaS security strategies to keep pace with emerging threats and technological advancements. Ultimately, by prioritizing security and privacy, SaaS providers can not only protect their users but also gain a competitive edge in the increasingly crowded market of cloud services.