scholarly journals Abordagens sobre computação na nuvem: uma breve revisão sobre segurança e privacidade aplicada a e-saúde no contexto do Programa Conecte SUS e Rede Nacional de Dados em Saúde (RNDS) / Approaches to cloud computing: a brief review of security and privacy applied to e-health in the context of the Connect SUS Program and the National Health Data Network (RNDS)

2021 ◽  
Vol 7 (4) ◽  
pp. 35152-35170
Author(s):  
Luís Rafaeli Coutinho ◽  
Henrique Pereira Oliveira d’Eça Neves ◽  
Lecian Cardoso Lopes
Keyword(s):  
Cloud Computing ◽  
National Health ◽  
Health Data ◽  
Security And Privacy ◽  
Data Network

Healthcare SaaS Based on a Data Model With Built-In Security and Privacy

2019 ◽  
pp. 744-759 ◽  
Author(s):  
Ruchika Asija ◽  
Rajarathnam Nallusamy
Keyword(s):  
Cloud Computing ◽  
Performance Evaluation ◽  
Data Model ◽  
Health Data ◽  
Software As A Service ◽  
Security And Privacy ◽  
Healthcare Industry ◽  
Access Controls ◽  
Software And Hardware ◽  
Security Levels

Cloud computing is a major technology enabler for providing efficient services at affordable costs by reducing the costs of traditional software and hardware licensing models. As it continues to evolve, it is widely being adopted by healthcare organisations. But hosting healthcare solutions on cloud is challenging in terms of security and privacy of health data. To address these challenges and to provide security and privacy to health data on the cloud, the authors present a Software-as-a-Service (SaaS) application with a data model with built-in security and privacy. This data model enhances security and privacy of the data by attaching security levels in the data itself expressed in the form of XML instead of relying entirely on application level access controls. They also present the performance evaluation of their application using this data model with different scaling indicators. To further investigate the adoption of IT and cloud computing in Indian healthcare industry they have done a survey of some major hospitals in India.

Healthcare SaaS Based on a Data Model with Built-In Security and Privacy

2016 ◽  
Vol 6 (3) ◽  
pp. 1-14 ◽  
Author(s):  
Ruchika Asija ◽  
Rajarathnam Nallusamy
Keyword(s):  
Cloud Computing ◽  
Performance Evaluation ◽  
Data Model ◽  
Health Data ◽  
Software As A Service ◽  
Security And Privacy ◽  
Healthcare Industry ◽  
Access Controls ◽  
Software And Hardware ◽  
Security Levels

Cloud computing is a major technology enabler for providing efficient services at affordable costs by reducing the costs of traditional software and hardware licensing models. As it continues to evolve, it is widely being adopted by healthcare organisations. But hosting healthcare solutions on cloud is challenging in terms of security and privacy of health data. To address these challenges and to provide security and privacy to health data on the cloud, the authors present a Software-as-a-Service (SaaS) application with a data model with built-in security and privacy. This data model enhances security and privacy of the data by attaching security levels in the data itself expressed in the form of XML instead of relying entirely on application level access controls. They also present the performance evaluation of their application using this data model with different scaling indicators. To further investigate the adoption of IT and cloud computing in Indian healthcare industry they have done a survey of some major hospitals in India.

Australia: Plans for national health data network

The Lancet ◽  
1992 ◽  
Vol 339 (8807) ◽  
pp. 1471-1472
Author(s):  
Nick Lush
Keyword(s):  
National Health ◽  
Health Data ◽  
Data Network

Issues in security and privacy of big data

2018 ◽  
Vol 7 (12) ◽  
pp. 1
Author(s):  
Shaveta Bhatia
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Approximate Method ◽  
Biomedical Research ◽  
Cyber Security ◽  
Data Science ◽  
Third Party ◽  
Security And Privacy ◽  
Security Threats ◽  
The Third

 The epoch of the big data presents many opportunities for the development in the range of data science, biomedical research cyber security, and cloud computing. Nowadays the big data gained popularity.  It also invites many provocations and upshot in the security and privacy of the big data. There are various type of threats, attacks such as leakage of data, the third party tries to access, viruses and vulnerability that stand against the security of the big data. This paper will discuss about the security threats and their approximate method in the field of biomedical research, cyber security and cloud computing.

Cloud computing security and privacy: Standards and regulations

2017 ◽  
Vol 54 ◽  
pp. 1-2 ◽  
Author(s):  
Yong Yu ◽  
Atsuko Miyaji ◽  
Man Ho Au ◽  
Willy Susilo
Keyword(s):  
Cloud Computing ◽  
Security And Privacy ◽  
Cloud Computing Security ◽  
Standards And Regulations

scholarly journals Data Security and Privacy in Cloud Computing

2014 ◽  
Vol 10 (7) ◽  
pp. 190903 ◽  
Author(s):  
Yunchuan Sun ◽  
Junsheng Zhang ◽  
Yongping Xiong ◽  
Guangyu Zhu
Keyword(s):  
Cloud Computing ◽  
Data Security ◽  
Security And Privacy

Proposed Back Propagation Deep Neural Network for Intrusion Detection in Internet of Things Fog Computing

2021 ◽  
Vol 9 (4) ◽  
pp. 464-469
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Intrusion Detection ◽  
Fog Computing ◽  
Denial Of Service ◽  
Back Propagation ◽  
Security And Privacy ◽  
Brute Force ◽  
Iot Platform ◽  
Proposed Model

Internet of things (IoT) is an emerging concept which aims to connect billions of devices with each other anytime regardless of their location. Sadly, these IoT devices do not have enough computing resources to process huge amount of data. Therefore, Cloud computing is relied on to provide these resources. However, cloud computing based architecture fails in applications that demand very low and predictable latency, therefore the need for fog computing which is a new paradigm that is regarded as an extension of cloud computing to provide services between end users and the cloud user. Unfortunately, Fog-IoT is confronted with various security and privacy risks and prone to several cyberattacks which is a serious challenge. The purpose of this work is to present security and privacy threats towards Fog-IoT platform and discuss the security and privacy requirements in fog computing. We then proceed to propose an Intrusion Detection System (IDS) model using Standard Deep Neural Network's Back Propagation algorithm (BPDNN) to mitigate intrusions that attack Fog-IoT platform. The experimental Dataset for the proposed model is obtained from the Canadian Institute for Cybersecurity 2017 Dataset. Each instance of the attack in the dataset is separated into separate files, which are DoS (Denial of Service), DDoS (Distributed Denial of Service), Web Attack, Brute Force FTP, Brute Force SSH, Heartbleed, Infiltration and Botnet (Bot Network) Attack. The proposed model is trained using a 3-layer BP-DNN

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