Research issues for privacy and security of electronic health services

Yüksel, Buket; Küpçü, Alptekin; Özkasap, Öznur

doi:10.1016/j.future.2016.08.011

Cited by 130 publications

(63 citation statements)

References 47 publications

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“…Reference [24] studies the identity exposure problem in cloud-based healthcare applications and proposes an anonymous authentication approach. However, cloud services are not fully trusted by users, due to the infrastructure security, data ownership, and vendor lock-in issues in cloud sourcing [7,25,26].…”

Section: Related Workmentioning

confidence: 99%

MedChain: Efficient Healthcare Data Sharing via Blockchain

2019

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Healthcare information exchange is an important research topic, which can benefit both healthcare providers and patients. In healthcare data sharing, many cloud-based solutions have been proposed, but the trustworthiness of a third-party cloud service is questionable. Recently, blockchain has been introduced in healthcare record sharing, which does not rely on trusting a third party. However, existing approaches only focus on the records collected from medical examination. They are not efficient in sharing data streams continuously generated from sensors and other monitoring devices. Today, IoT devices have been widely deployed and sensors and mobile applications can monitor patients’ body conditions. The collected data are shared to laboratories and institutions for diagnosis and further study. Moreover, existing approaches are too rigid to efficiently support metadata change. In this paper, an efficient data-sharing scheme is proposed, called MedChain, which combines blockchain, digest chain, and structured P2P network techniques to overcome the above efficiency issues in the existing approaches for sharing both types of healthcare data. Based on MedChain, a session-based healthcare data-sharing scheme is devised, which brings flexibility in data sharing. The evaluation results show that MedChain can achieve higher efficiency and satisfy the security requirements in data sharing.

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Section: Related Workmentioning

confidence: 99%

MedChain: Efficient Healthcare Data Sharing via Blockchain

2019

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“…These solutions were helpful at some extent in offering various security requirements under desired healthcare scenarios. However, with the current advancement in healthcare technology, these approaches are not just sufficient because the patient has been exploited by various stakeholders through different means and without their consent [11], [12]. In this context, researchers are keen to find various secure solutions based on blockchain based healthcare approaches [13].…”

Section: Related Workmentioning

confidence: 99%

Secure and Efficient Data Accessibility in Blockchain Based Healthcare Systems

Ramani

Kumar

Bracken

et al. 2018

2018 IEEE Global Communications Conference (GLOBECOM)

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The healthcare industry is constantly reforming and adopting new shapes with respect to the technological evolutions and transitions. One of the crucial requirements in the current smart healthcare systems is the protection of patients sensitive data against the potential adversaries. Therefore, it is vital to have secure data access mechanisms that can ensure only authorized entities can access the patients medical information. Hence, this paper considers blockchain technology as a distributed approach protect the data in healthcare systems. This research proposes a blockchain based secure and efficient data accessibility mechanism for the patient and the doctor in a given healthcare system. Proposed system able to protect the privacy of the patients as well. The security analysis of our scheme shows that it can resist to well-known attacks along with maintaining the integrity of the system. Moreover, an Ethereum based implementation has used to verify the feasibility of our proposed system.

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“…After the sequencing process, the produced reads are typically used either in a de novo assembly, or aligned to a reference genome. Besides the wide use of genomic data on diverse fields, privacy attacks [8], [22] and the use of clouds environments for biomedical data analysis [23], [24], [25], [26] have raised concerns about the data security on the alignment step. Melissa Gymrek et al [5] performed a re-identification attack identifying 131 of the anonymized genomes of the 1000 Genomes Project.…”

Section: Related Workmentioning

confidence: 99%

Sensitivity Levels: Optimizing the Performance of Privacy Preserving DNA Alignment

Fernandes

Decouchant

Voelp

et al. 2018

Preprint

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The advent of high throughput next-generation sequencing (NGS) machines made DNA sequencing cheaper, but also put pressure on the genomic life-cycle, which includes aligning millions of short DNA sequences, called reads, to a reference genome. On the performance side, efficient algorithms have been developed, and parallelized on public clouds. On the privacy side, since genomic data are utterly sensitive, several cryptographic mechanisms have been proposed to align reads securely, with a lower performance than the former, which in turn are not secure. This manuscript proposes a novel contribution to improving the privacy × performance product in current genomic studies. Building on recent works that argue that genomics data needs to be treated according to a threat-risk analysis, we introduce a multi-level sensitivity classification of genomic variations. Our classification prevents the amplification of possible privacy attacks, thanks to promoting and partitioning mechanisms among sensitivity levels. Thanks to this classification, reads can be aligned, stored, and later accessed, using different security levels. We then extend a recent filter, which detects the reads that carry sensitive information, to classify reads into sensitivity levels. Finally, based on a review of the existing alignment methods, we show that adapting alignment algorithms to reads sensitivity allows high performance gains, whilst enforcing high privacy levels. Our results indicate that using sensitivity levels is feasible to optimize the performance of privacy preserving alignment, if one combines the advantages of private and public clouds.

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Research issues for privacy and security of electronic health services

Cited by 130 publications

References 47 publications

MedChain: Efficient Healthcare Data Sharing via Blockchain

MedChain: Efficient Healthcare Data Sharing via Blockchain

Secure and Efficient Data Accessibility in Blockchain Based Healthcare Systems

Sensitivity Levels: Optimizing the Performance of Privacy Preserving DNA Alignment

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