Data security and privacy in E-health Cloud: Comparative study

Oukid-Khouas, Saliha; Benblidia, Nadjia

doi:10.1145/2816839.2816930

Cited by 5 publications

(9 citation statements)

References 8 publications

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“…Vertical data partition that is performed at owner side provides fixed vertical partition of medical data. (2). Data merging process for health dataset access at the authorized recipient side.…”

Section: Role and Time-based Access Controlmentioning

confidence: 99%

“…Medicinal records (EHRs) holding patient data may belong to various health organizations. EHRs ought to be accessible anytime and at anyplace, permitting healthcare providers to provide proper patients healthcare investigation and medical treatment [2]. The quality of Service (QoS) of medical records directly depends upon medical device used for diagnosis purpose in health institutions.…”

Section: Quality Of Service (Qos)mentioning

confidence: 99%

“…There are also many secondary uses such as public health, clinical research, and statistics. We focus our work on the secondary use of EHR [1,2,3]. ___________________________________________________________________________ Abid Khan* abk15@aber.ac.uk [Corresponding author] privacy issues that arise in cloud-based EHRs may not be the same as applied to privacy preserved EHRs using standard privacy techniques, it is due to the highly dynamic and distributed environment of cloud-based systems.…”

Section: Introductionmentioning

confidence: 99%

“…Some other information may also be viewed as sensitive such as private fiscal information, job performance report and personally identifiable information e.g. biometric information[2].4.3 Cloud Specific Privacy RequirementsPrivacy requirements like information consistency and quality of service relate to the fundamental aspects of information security. By following these requirements, a privacy technique can further enhance the privacy vs. utility trade-off in the outsourced data.4.3.1 Information Consistency (IC)Different versions of patients EHRs exist for different personnel like health professionals.…”

mentioning

confidence: 99%

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Privacy preservation in e-health cloud: taxonomy, privacy requirements, feasibility analysis, and opportunities

2020

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Electronic health records (EHRs) are increasingly employed to maintain, store and share varied types of patient data. The data can also be utilized for various research purposes, such as clinical trials or epidemic control strategies. With the increasing cost and scarcity of healthcare services, healthcare organizations feel at ease in outsourcing these services to cloud-based EHRs. That serves as pay-as-you-go (PAYG) "e-health cloud" models to aid the healthcare organizations handling with existing and imminent demands yet restricting their costs. Technologies can host some risks; hence the privacy of information in these systems is of utmost importance. Regardless of its increased effectiveness and growing eagerness in its adoption, not much care is being employed to the privacy issues that might arise. Privacy preservation need to be reviewed about the changing privacy rules and legislations regarding sensitive personal data. Our work aims at answering three major questions: firstly, how privacy models and privacy techniques correlate with each other, secondly, how we can fix the privacy-utility-trade off by using different combinations of privacy models and privacy techniques and lastly, what are the most relevant privacy techniques that can be adapted to achieve privacy of EHR on cloud.

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Section: Role and Time-based Access Controlmentioning

confidence: 99%

Section: Quality Of Service (Qos)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Privacy preservation in e-health cloud: taxonomy, privacy requirements, feasibility analysis, and opportunities

2020

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“…In addition, when the government designs public sports resource allocation strategy documents, the government also considers the local resident health records to increase the degree of the people's sport participation, so the designed public sports resource allocation strategy documents may contain partial health data information [21]. Thus, the administrator of the document database needs to protect the residents' health data information.…”

Section: Related Workmentioning

confidence: 99%

Fuzzy Keywords-Driven Public Sports Resource Allocation Strategies Retrieval With Privacy-Preservation

Sang

Zhang

et al. 2020

IEEE Access

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Currently, the government proposes various public sports resource allocation strategies to promote the construction of public sports in the local. Thus, searching for the document database becomes an economic and efficient way for government officials to understand the contents of various public sports resource allocation strategies. As the government officials lack background knowledge of public sports resource allocation, the government officials are hard to retrieve appropriate documents. What's more, the document database is generally unwilling to share all text document information with the government official as some documents contain sensitive data information. Considering the above drawbacks, we put forward a fuzzy keywords-driven public sports resource allocation strategies retrieval approach based on the Simhash (named PSRASk+S) in the paper. The retrieval approach can accurately recommend appropriate documents to the government officials, by using the text description mining of documents and the fuzzy keywords search technology. Furthermore, the retrieval process is not revealing the sensitive data information of the irrelevant public sports resource allocation strategy document to the government officials, so the retrieval process can achieve local information protection mechanism. Finally, a case study explains the feasibility and effectiveness of our retrieval approach step by step.

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