2016
DOI: 10.14569/ijacsa.2016.070933
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Security and Privacy Issues in Ehealthcare Systems: Towards Trusted Services

Abstract: Abstract-Recent years have witnessed a widespread availability of electronic healthcare data record (EHR) systems. Vast amounts of health data were generated in the process of treatment in medical centers such hospitals, clinics, or other institutions. To improve the quality of healthcare service, EHRs could be potentially shared by a variety of users. This results in significant privacy issues that should be addressed to make the use of EHR practical. In fact, despite the recent research in designing standard… Show more

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Cited by 12 publications
(7 citation statements)
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“…System availability looks at the period of up-time for operations and is a measure of how often the system is alive and well. It is always denoted as (up-time)/(up-time + downtime) with numerous variants (Ahmed & Mousa, 2016). Up-time and downtime refer to dichotomized conditions.…”
Section: Availabilitymentioning
confidence: 99%
“…System availability looks at the period of up-time for operations and is a measure of how often the system is alive and well. It is always denoted as (up-time)/(up-time + downtime) with numerous variants (Ahmed & Mousa, 2016). Up-time and downtime refer to dichotomized conditions.…”
Section: Availabilitymentioning
confidence: 99%
“…Class conditional independence is also included, where correlations between class attributes are ignored. [30], [31] mentioned that many researchers found that Naïve Bayes has excellence performance in terms of computational efficiency since it has better performance than other algorithms; Decision Tree and neural networks which can handle missing data and produce high prediction accuracy.…”
Section: ) Naïve Bayesmentioning
confidence: 99%
“…Furthermore, this model is easy to build because it uses the probabilistic conditional approach to analyse datasets by multiplying the individual probabilities of each pair of value attributes, which will help the user derive more functionality from the data without being over-fitted even for large datasets [30], [25]. This classifier is very stable; it can be trained with small datasets to create accurate parameter predictions since it only needs the calculation from the frequencies and the outcomes of the pairs of attributes in the training datasets [32], [27].…”
Section: ) Naïve Bayesmentioning
confidence: 99%
“…This environment is called telemedicine. Additionally, researchers address security and privacy issues in the eHealthcare system in relation to the Electronic Healthcare data Record (EHR) [6]. The authors focus to provide a framework for the scenario of data transmission in the world of eHealthcare with wireless body sensors, connected to a medical server system.…”
Section: B Security and Privacy In Healthcare Environmentmentioning
confidence: 99%