scholarly journals Multilevel Privacy Assurance Evaluation of Healthcare Metadata

2021 ◽  
Vol 11 (22) ◽  
pp. 10686
Author(s):  
Syeda Amna Sohail ◽  
Faiza Allah Bukhsh ◽  
Maurice van Keulen
Keyword(s):  
Privacy Preservation ◽  
Process Mining ◽  
Research Work ◽  
Healthcare Providers ◽  
Conceptual Modeling ◽  
Empirical Evaluation ◽  
Healthcare Services ◽  
Privacy Preserving ◽  
Third Party ◽  
Conformance Checking

Healthcare providers are legally bound to ensure the privacy preservation of healthcare metadata. Usually, privacy concerning research focuses on providing technical and inter-/intra-organizational solutions in a fragmented manner. In this wake, an overarching evaluation of the fundamental (technical, organizational, and third-party) privacy-preserving measures in healthcare metadata handling is missing. Thus, this research work provides a multilevel privacy assurance evaluation of privacy-preserving measures of the Dutch healthcare metadata landscape. The normative and empirical evaluation comprises the content analysis and process mining discovery and conformance checking techniques using real-world healthcare datasets. For clarity, we illustrate our evaluation findings using conceptual modeling frameworks, namely e3-value modeling and REA ontology. The conceptual modeling frameworks highlight the financial aspect of metadata share with a clear description of vital stakeholders, their mutual interactions, and respective exchange of information resources. The frameworks are further verified using experts’ opinions. Based on our empirical and normative evaluations, we provide the multilevel privacy assurance evaluation with a level of privacy increase and decrease. Furthermore, we verify that the privacy utility trade-off is crucial in shaping privacy increase/decrease because data utility in healthcare is vital for efficient, effective healthcare services and the financial facilitation of healthcare enterprises.

scholarly journals Privacy-preserving energy storage sharing with blockchain and secure multi-party computation

2021 ◽  
Vol 1 (1) ◽  
pp. 32-50
Author(s):  
Nan Wang ◽  
Sid Chi-Kin Chau ◽  
Yue Zhou
Keyword(s):  
Energy Storage ◽  
Energy Demand ◽  
Empirical Evaluation ◽  
Privacy Preserving ◽  
Third Party ◽  
User Privacy ◽  
External Energy ◽  
Novel Approach ◽  
Significant Cost Reduction ◽  
The Cost

Energy storage provides an effective way of shifting temporal energy demands and supplies, which enables significant cost reduction under time-of-use energy pricing plans. Despite its promising benefits, the cost of present energy storage remains expensive, presenting a major obstacle to practical deployment. A more viable solution to improve the cost-effectiveness is by sharing energy storage, such as community sharing, cloud energy storage and peer-to-peer sharing. However, revealing private energy demand data to an external energy storage operator may compromise user privacy, and is susceptible to data misuses and breaches. In this paper, we explore a novel approach to support energy storage sharing with privacy protection, based on privacy-preserving blockchain and secure multi-party computation. We present an integrated solution to enable privacy-preserving energy storage sharing, such that energy storage service scheduling and cost-sharing can be attained without the knowledge of individual users' demands. It also supports auditing and verification by the grid operator via blockchain. Furthermore, our privacy-preserving solution can safeguard against a majority of dishonest users, who may collude in cheating, without requiring a trusted third-party. We implemented our solution as a smart contract on real-world Ethereum blockchain platform, and provided empirical evaluation in this paper 1 .

scholarly journals Framework to Avoid Similarity Attack in Big Streaming Dat

2018 ◽  
Vol 8 (5) ◽  
pp. 2920
Author(s):  
Ganesh Dagadu Puri ◽  
D. Haritha
Keyword(s):  
Privacy Preservation ◽  
Privacy Preserving ◽  
Streaming Data ◽  
Third Party ◽  
Stream Data ◽  
Distributed Environment ◽  
Market Sentiment ◽  
Replacement Technique ◽  
Electronic Health ◽  
Health Applications

<span>The existing methods for privacy preservation are available in variety of fields like social media, stock market, sentiment analysis, electronic health applications. The electronic health dynamic stream data is available in large quantity. Such large volume stream data is processed using delay free anonymization framework. Scalable privacy preserving techniques are required to satisfy the needs of processing large dynamic stream data. In this paper privacy preserving technique which can avoid similarity attack in big streaming data is proposed in distributed environment. It can process the data in parallel to reduce the anonymization delay.  In this paper the replacement technique is used for avoiding similarity attack. Late validation technique is used to reduce information loss. The application of this method is in medical diagnosis, e-health applications, health data processing at third party.</span>

scholarly journals Privacy preservation Models for Third-Party Auditor over Cloud Computing: a Survey

2021 ◽  
Author(s):  
Abdul Razaque ◽  
Mohamed Frej ◽  
Bandar Alotaibi ◽  
Munif Alotaibi
Keyword(s):  
Cloud Computing ◽  
Privacy Preservation ◽  
Service Providers ◽  
Personal Information ◽  
Cloud Service ◽  
Privacy Preserving ◽  
Third Party ◽  
Security Requirements ◽  
Security Threats ◽  
State Of Art

Cloud computing has become a prominent technology due to its important utility service; this service concentrates on outsourcing data to organizations and individual consumers. Cloud computing has considerably changed the manner in which individuals or organizations store, retrieve, and organize their personal information. Despite the manifest development in cloud computing, there are still some concerns regarding the level of security and issues related to adopting cloud computing that prevent users from fully trusting this useful technology. Hence, for the sake of reinforcing the trust between Cloud Clients (CC) and Cloud Service Providers (CSP), as well as safeguarding the CC’s data in the cloud, several security paradigms of cloud computing based on a Third-Party Auditor (TPA) have been introduced. The TPA, as a trusted party, is responsible for checking the integrity of the CC’s data and all the critical information associated with it. However, the TPA could become an adversary and could aim to deteriorate the privacy of the CC’s data by playing a malicious role. In this paper, we present the state-of-art of cloud computing’s privacy-preserving models (PPM) based on a TPA. Three TPA factors of paramount significance have been discussed: TPA involvement, security requirements, and security threats caused by vulnerabilities. Moreover, TPA’s privacy preserving models have been comprehensively analyzed and categorized into different classes with an emphasis on their dynamicity. Finally, we discuss the limitations of the models and present our recommendations for their improvement.

scholarly journals Assessing Quality of Healthcare Delivery When Making Choices: National Survey on Health Consumers’ Decision Making Practices

2021 ◽  
Vol 16 (1) ◽  
pp. 11-20
Author(s):  
Mark Avery ◽  
Allan Cripps ◽  
Gary D Rogers
Keyword(s):  
Decision Making ◽  
Healthcare Delivery ◽  
Healthcare Providers ◽  
Quality Of Healthcare ◽  
Healthcare Services ◽  
Third Party ◽  
Healthcare Needs ◽  
Interpersonal Engagement ◽  
And Performance

Objective: Choices and quality decisions made by consumers in relation to their healthcare have been associated with personal experience of those services, interpersonal engagement and reliance on third-party information, as well as the subsequent satisfaction with the service. The purpose of this research was to understand current information sources, determinants of quality discernment and decision-making factors by consumers in the Australian community in relation to healthcare. Method:  Conventional content analysis research was undertaken in the form of a national telephone survey of 200 consumers. Open-ended questions were used to elicit information from the general community. Results: Reputation and other key interpersonal and structural elements are utilised in determining quality of healthcare services as well as in deployment as key factors in decision-making regarding use of healthcare services. While most respondents valued and used key information about provider relationships, outcomes performance and performance rankings, up to 20% of respondents did not know or could not identify ways in which they would assess and evaluate the quality of healthcare services. Conclusion: This research identifies that consumers use a range of information and advice relating to experience, interpersonal engagement and information from third-party sources. If healthcare providers develop clearer communications around their technical, procedural and conduct principles, consumers will be in a better position to evaluate reputation and make decisions about their healthcare needs and the health system.

Privacy-Preserving Data Mining

2009 ◽  
pp. 527-536 ◽  
Author(s):  
Alexandre Evfimievski ◽  
Tyrone Grandison
Keyword(s):  
Data Mining ◽  
Privacy Preservation ◽  
Statistical Processing ◽  
Privacy Preserving ◽  
Third Party ◽  
Data Publishing ◽  
Sensitive Information ◽  
Public Servants ◽  
Data Set ◽  
Privacy Preserving Data Mining

Privacy-preserving data mining (PPDM) refers to the area of data mining that seeks to safeguard sensitive information from unsolicited or unsanctioned disclosure. Most traditional data mining techniques analyze and model the data set statistically, in aggregated form, while privacy preservation is primarily concerned with protecting against disclosure of individual data records. This domain separation points to the technical feasibility of PPDM. Historically, issues related to PPDM were first studied by the national statistical agencies interested in collecting private social and economical data, such as census and tax records, and making it available for analysis by public servants, companies, and researchers. Building accurate socioeconomical models is vital for business planning and public policy. Yet, there is no way of knowing in advance what models may be needed, nor is it feasible for the statistical agency to perform all data processing for everyone, playing the role of a trusted third party. Instead, the agency provides the data in a sanitized form that allows statistical processing and protects the privacy of individual records, solving a problem known as privacypreserving data publishing. For a survey of work in statistical databases, see Adam and Wortmann (1989) and Willenborg and de Waal (2001).

scholarly journals SmartMedChain: A Blockchain-Based Privacy-Preserving Smart Healthcare Framework

2021 ◽  
Vol 2021 ◽  
pp. 1-19
Author(s):  
Driss El Majdoubi ◽  
Hanan El Bakkali ◽  
Souad Sadki
Keyword(s):  
Data Storage ◽  
Healthcare Providers ◽  
Security Analysis ◽  
Data Access ◽  
Healthcare Services ◽  
Privacy Preserving ◽  
Security And Privacy ◽  
Distributed Data Storage ◽  
Smart Healthcare ◽  
Data Access Control

Nowadays, the adoption of Internet of Things (IoT) technology worldwide is accelerating the digital transformation of healthcare industry. In this context, smart healthcare (s-healthcare) solutions are ensuring better and innovative opportunities for healthcare providers to improve patients’ care. However, these solutions raise also new challenges in terms of security and privacy due to the diversity of stakeholders, the centralized data management, and the resulting lack of trustworthiness, accountability, and control. In this paper, we propose an end-to-end Blockchain-based and privacy-preserving framework called SmartMedChain for data sharing in s-healthcare environment. The Blockchain is built on Hyperledger Fabric and stores encrypted health data by using the InterPlanetary File System (IPFS), a distributed data storage solution with high resiliency and scalability. Indeed, compared to other propositions and based on the concept of smart contracts, our solution combines both data access control and data usage auditing measures for both Medical IoT data and Electronic Health Records (EHRs) generated by s-healthcare services. In addition, s-healthcare stakeholders can be held accountable by introducing an innovative Privacy Agreement Management scheme that monitors the execution of the service in respect of patient preferences and in accordance with relevant privacy laws. Security analysis and experimental results show that the proposed SmartMedChain is feasible and efficient for s-healthcare environments.

scholarly journals Privacy Preservation Models for Third-Party Auditor over Cloud Computing: A Survey

Electronics ◽  
2021 ◽  
Vol 10 (21) ◽  
pp. 2721
Author(s):  
Abdul Razaque ◽  
Mohamed Ben Haj Frej ◽  
Bandar Alotaibi ◽  
Munif Alotaibi
Keyword(s):  
Cloud Computing ◽  
Privacy Preservation ◽  
Service Providers ◽  
State Of The Art ◽  
Personal Information ◽  
Cloud Service ◽  
Privacy Preserving ◽  
Third Party ◽  
Security Requirements ◽  
Security Threats

Cloud computing has become a prominent technology due to its important utility service; this service concentrates on outsourcing data to organizations and individual consumers. Cloud computing has considerably changed the manner in which individuals or organizations store, retrieve, and organize their personal information. Despite the manifest development in cloud computing, there are still some concerns regarding the level of security and issues related to adopting cloud computing that prevent users from fully trusting this useful technology. Hence, for the sake of reinforcing the trust between cloud clients (CC) and cloud service providers (CSP), as well as safeguarding the CC’s data in the cloud, several security paradigms of cloud computing based on a third-party auditor (TPA) have been introduced. The TPA, as a trusted party, is responsible for checking the integrity of the CC’s data and all the critical information associated with it. However, the TPA could become an adversary and could aim to deteriorate the privacy of the CC’s data by playing a malicious role. In this paper, we present the state of the art of cloud computing’s privacy-preserving models (PPM) based on a TPA. Three TPA factors of paramount significance are discussed: TPA involvement, security requirements, and security threats caused by vulnerabilities. Moreover, TPA’s privacy preserving models are comprehensively analyzed and categorized into different classes with an emphasis on their dynamicity. Finally, we discuss the limitations of the models and present our recommendations for their improvement.

Topical issues of medical malpractices

2014 ◽  
Vol 155 (38) ◽  
pp. 1510-1516
Author(s):  
Tamás Heiner ◽  
Tímea Barzó
Keyword(s):  
Medical Malpractice ◽  
Medical Service ◽  
Early Stage ◽  
Healthcare Providers ◽  
Healthcare Services ◽  
Practical Experience ◽  
Current Analysis ◽  
Breach Of Contract ◽  
Judicial Decisions ◽  
Contractual Relationship

The number of medical malpractice lawsuits filed each year in Hungary has considerably increased since 1990. The judicial decisions and practices on determining and awarding wrongful damages recoverable for medical malpractices in the Hungarian civil law have been developing for decades. In the meantime, a new Hungarian Civil Code (Act V of 2013) has entered into force, which among others, necessitates the revaluation of assessment of damages recoverable for medical malpractices. There are two main areas where fundamental changes have been introduced, which may significantly affect the outcome of medical malpractice lawsuits in the future. In the early stage of medical malpractices it was unclear whether the courts had to consider either the contractual relationship between patients and healthcare providers (contractual liability) or general codal articles on damages arising from non-contractual liability/torts (delictual liability) in their judgement delivered in the cases. Both the theoretical and practical experience of the last ten years shows that healthcare services agreements are concluded between healthcare providers and patients with the aim and intention to provide appropriate professional healthcare services to patients, which meet patients’ interests and wishes. The medical service is violated if it fails to meet patients’ interests and wishes as well as the objectives of the agreement. Since the new legislation implies a stricter liability for damages in the case of breach of contract and stricter rules for exempting the party in breach from compensation obligations, the opportunities to exempt healthcare providers from these obligations have become limited compared to previous regulations. This modification, which was aimed at further integrating the established judicial practices into legislation, stipulates the application of the rules for liability for damages resulting from medical malpractice in non-contractual situations. This paper analyses dogmatic and practical problems related to this topic. Another important area of current analysis is the institution of injury fees, which replaced the reimbursement of non-pecuniary damages. The mere fact of infringement allows setting injury fees. Taking into consideration the current resources in staff and equipment available in healthcare, this regulation may promote claims for injury fees impartial. Consequently, courts will have to apply other criteria when judgment in ‘trivial cases’, which might not require legal assessment, is delivered. Orv. Hetil., 2014, 155(38), 1510–1516.

Survey of Cloud Computing in Healthcare Sector

2017 ◽  
Vol 7 (7) ◽  
pp. 337
Author(s):  
S. Karthiga Devi ◽  
B. Arputhamary
Keyword(s):  
Cloud Computing ◽  
Healthcare Providers ◽  
High Volume ◽  
Healthcare Services ◽  
Healthcare Sector ◽  
Cloud Infrastructure ◽  
Healthcare Organizations ◽  
Privacy And Security ◽  
Healthcare Data ◽  
Number Of Patients

Today the volume of healthcare data generated increased rapidly because of the number of patients in each hospital increasing.  These data are most important for decision making and delivering the best care for patients. Healthcare providers are now faced with collecting, managing, storing and securing huge amounts of sensitive protected health information. As a result, an increasing number of healthcare organizations are turning to cloud based services. Cloud computing offers a viable, secure alternative to premise based healthcare solutions. The infrastructure of Cloud is characterized by a high volume storage and a high throughput. The privacy and security are the two most important concerns in cloud-based healthcare services. Healthcare organization should have electronic medical records in order to use the cloud infrastructure. This paper surveys the challenges of cloud in healthcare and benefits of cloud techniques in health care industries.

scholarly journals Adopt, adapt, or abandon technology-supported person-centred care initiatives: healthcare providers’ beliefs matter

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Kari Dyb ◽  
Gro Rosvold Berntsen ◽  
Lisbeth Kvam
Keyword(s):  
Information Technologies ◽  
Scale Up ◽  
Healthcare Providers ◽  
Healthcare Services ◽  
Analytical Framework ◽  
Development Project ◽  
Technology Support ◽  
Care Needs ◽  
Term Care

Abstract Background Technology support and person-centred care are the new mantra for healthcare programmes in Western societies. While few argue with the overarching philosophy of person-centred care or the potential of information technologies, there is less agreement on how to make them a reality in everyday clinical practice. In this paper, we investigate how individual healthcare providers at four innovation arenas in Scandinavia experienced the implementation of technology-supported person-centred care for people with long-term care needs by using the new analytical framework nonadoption, abandonment, and challenges to the scale-up, spread, and sustainability (NASSS) of health and care technologies. We also discuss the usability and sensitivity of the NASSS framework for those seeking to plan, implement, and evaluate technology-supported healthcare programmes. This study is part of an interdisciplinary research and development project called Patients and Professionals in Partnership (2016–2020). It originates at one of ten work packages in this project. Method The main data consist of ethnographic field observations at the four innovation arenas and 29 interviews with involved healthcare providers. To ensure continuous updates and status on work in the four innovation arenas, we have also participated in a total of six annual network meetings arranged by the project. Results While the NASSS framework is very useful for identifying and communicating challenges with the adoption and spread of technology-supported person-centred care initiatives, we found it less sensitive towards capturing the dedication, enthusiasm, and passion for care transformation that we found among the healthcare providers in our study. When it comes to technology-supported person-centred care, the point of no return has passed for the involved healthcare providers. To them, it is already a definite part of the future of healthcare services. How to overcome barriers and obstacles is pragmatically approached. Conclusion Increased knowledge about healthcare providers and their visions as potential assets for care transformation might be critical for those seeking to plan, implement, and evaluate technology-supported healthcare programmes.

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