Accessing medical image file with co-allocation HDFS in cloud

Yang, Chao-Tung; Shih, Wen-Chung; Chen, Lung-Teng; Kuo, Cheng-Ta; Jiang, Fuu-Cheng; Leu, Fang−Yie

doi:10.1016/j.future.2014.08.008

Cited by 44 publications

(11 citation statements)

References 32 publications

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“…This relates to the need for efficient security mechanisms, with the wide range of security requirements among healthcare providers, the hospital's security requirements and policies must be fully reflected in cloud services. This service should not lead to high computation and involve high communication costs rendering them incompetent in the cloud [11]. In addition, the cloud should be very flexible in adding new needed services to support healthcare processes.…”

Section: Discussionmentioning

confidence: 99%

Factors Limiting the Adoption of Cloud Computing in Teleradiology

Akinsanya¹,

Papadaki²,

Sun³

2019

IJISR

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Cloud-based medical data sharing continues to change the way healthcare is conducted in hospitals. It is significantly supporting the 'patient-centricity' trend in providing medical services, and provides clinical team-based care delivery, clinical research, and point-of-care access to demographic and medical information, regardless of the location of the patient and the medical practitioners. Despite these benefits of cloud-based medical data sharing, the adoption in healthcare seems rather limited mainly due to security concerns. The significant contribution of this paper focuses on the identification and comparison of technical security and organizational factors that aids limited adoption of Cloud in teleradiology. Data was collected from relevant healthcare practitioners through interview conducted over the telephone and supported by a form of open-ended questions. The analysis revealed that against popular opinion, organizational factors such as Economics and Adoption Costs, Cultural Resistance, and Legal Rules, were major limiting factors. Future research will focus on proposing a cloud medical data sharing maturity model, which would support healthcare organizations to benchmark, assess and eventually improve the related services.

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Section: Discussionmentioning

confidence: 99%

Factors Limiting the Adoption of Cloud Computing in Teleradiology

Akinsanya¹,

Papadaki²,

Sun³

2019

IJISR

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“…For example, there is a proposal for a security model for G-Hadoop (an extension of the MapReduce framework to run on multiple clusters) that simplifies users' authentication and some security mechanisms in order to protect the system from traditional attacks [27]. A few papers focus on protecting the data that is stored in the HDFS by proposing a new schema [24], a secure access system [28], or even the creation of an encryption scheme [29].…”

Section: Security For Hadoopmentioning

confidence: 99%

Main Issues in Big Data Security

2016

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Data is currently one of the most important assets for companies in every field. The continuous growth in the importance and volume of data has created a new problem: it cannot be handled by traditional analysis techniques. This problem was, therefore, solved through the creation of a new paradigm: Big Data. However, Big Data originated new issues related not only to the volume or the variety of the data, but also to data security and privacy. In order to obtain a full perspective of the problem, we decided to carry out an investigation with the objective of highlighting the main issues regarding Big Data security, and also the solutions proposed by the scientific community to solve them. In this paper, we explain the results obtained after applying a systematic mapping study to security in the Big Data ecosystem. It is almost impossible to carry out detailed research into the entire topic of security, and the outcome of this research is, therefore, a big picture of the main problems related to security in a Big Data system, along with the principal solutions to them proposed by the research community.

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“…Nowadays, medicine is relying much more on specific data collection and analysis, whereas medical knowledge is explosively growing. Therefore, medical knowledge published and shared via cloud is popular in practice [21], [22]. Patients typically will know more than a doctor.…”

Section: A Design Issuesmentioning

confidence: 99%

Health Care Virtual Environment System Reinforced by Hadoop and Cloud

Vidyashree¹

2016

IJECS

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Abstract-The advances in information technology have wit-nessed great progress on healthcare technologies in various do-mains nowadays. However, these new technologies have also made healthcare data not only much bigger but also much more difficult to handle and process. Moreover, because the data are created from a variety of devices within a short time span, the character-istics of these data are that they are stored in different formats and created quickly, which can, to a large extent, be regarded as a big data problem. To provide a more convenient service and environment of healthcare, this paper proposes a cyber-physical system for patient-centric healthcare applications and services, called Health-CPS, built on cloud and big data analytics technolo-gies. This system consists of a data collection layer with a unified standard, a data management layer for distributed storage and parallel computing, and a data-oriented service layer. The results of this study show that the technologies of cloud and big data can be used to enhance the performance of the healthcare system so that humans can then enjoy various smart healthcare applications and services.

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Accessing medical image file with co-allocation HDFS in cloud

Cited by 44 publications

References 32 publications

Factors Limiting the Adoption of Cloud Computing in Teleradiology

Factors Limiting the Adoption of Cloud Computing in Teleradiology

Main Issues in Big Data Security

Health Care Virtual Environment System Reinforced by Hadoop and Cloud

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