The future of healthcare in Singapore. How an integrated use of A.I., Internet-of-Medical things (IoMT), Blockchain-based technologies, and Cloud-computing-based Medtech and Digital Health solutions will radically address medical data integrity concerns.

2021 ◽  
Author(s):  
Jezon Ow
Keyword(s):  
Cloud Computing ◽  
Digital Health ◽  
Data Integrity ◽  
Medical Data ◽  
The Future ◽  
Internet Of Medical Things

scholarly journals The future of digital health with federated learning

2020 ◽  
Vol 3 (1) ◽  
Author(s):  
Nicola Rieke ◽  
Jonny Hancox ◽  
Wenqi Li ◽  
Fausto Milletarì ◽  
Holger R. Roth ◽  
...  
Keyword(s):  
Statistical Models ◽  
Digital Health ◽  
Healthcare Systems ◽  
Medical Data ◽  
Data Driven ◽  
Full Potential ◽  
Sufficient Data ◽  
Key Factors ◽  
Privacy Concerns ◽  
The Future

Abstract Data-driven machine learning (ML) has emerged as a promising approach for building accurate and robust statistical models from medical data, which is collected in huge volumes by modern healthcare systems. Existing medical data is not fully exploited by ML primarily because it sits in data silos and privacy concerns restrict access to this data. However, without access to sufficient data, ML will be prevented from reaching its full potential and, ultimately, from making the transition from research to clinical practice. This paper considers key factors contributing to this issue, explores how federated learning (FL) may provide a solution for the future of digital health and highlights the challenges and considerations that need to be addressed.

Data Integrity Techniques in Cloud Computing: An Analysis

2017 ◽  
Vol 7 (8) ◽  
pp. 121 ◽  
Author(s):  
Neha Thakur ◽  
Aman Kumar Sharma
Keyword(s):  
Cloud Computing ◽  
Cloud Storage ◽  
Data Integrity ◽  
Advantages And Disadvantages ◽  
Security Models ◽  
Cloud Storage Service ◽  
Storage Service ◽  
Cloud Users ◽  
It Enterprises

Cloud computing has been envisioned as the definite and concerning solution to the rising storage costs of IT Enterprises. There are many cloud computing initiatives from IT giants such as Google, Amazon, Microsoft, IBM. Integrity monitoring is essential in cloud storage for the same reasons that data integrity is critical for any data centre. Data integrity is defined as the accuracy and consistency of stored data, in absence of any alteration to the data between two updates of a file or record.  In order to ensure the integrity and availability of data in Cloud and enforce the quality of cloud storage service, efficient methods that enable on-demand data correctness verification on behalf of cloud users have to be designed. To overcome data integrity problem, many techniques are proposed under different systems and security models. This paper will focus on some of the integrity proving techniques in detail along with their advantages and disadvantages.

An examination on data integrity auditing patterns in cloud computing

2018 ◽  
Vol 7 (1.9) ◽  
pp. 200
Author(s):  
T A.Mohanaprakash ◽  
J Andrews
Keyword(s):  
Cloud Computing ◽  
Information Security ◽  
Data Integrity ◽  
Cloud Service ◽  
New Approach ◽  
Computing Services ◽  
Security Challenges ◽  
Cloud Server ◽  
State Of Affairs ◽  
Dynamic Updates

Cloud computing is associate inclusive new approach on however computing services square measure made and utilized. Cloud computing is associate accomplishment of assorted styles of services that has attracted several users in today’s state of affairs. The foremost enticing service of cloud computing is information outsourcing, because of this the information homeowners will host any size of information on the cloud server and users will access the information from cloud server once needed. A dynamic outsourced auditing theme that cannot solely defend against any dishonest entity and collision, however conjointly support verifiable dynamic updates to outsourced information. The new epitome of information outsourcing conjointly faces the new security challenges. However, users might not totally trust the cloud service suppliers (CSPs) as a result of typically they may be dishonest. It's tough to work out whether or not the CSPs meet the customer’s expectations for information security. Therefore, to with success maintain the integrity of cloud information, several auditing schemes are projected. Some existing integrity ways will solely serve for statically archived information and a few auditing techniques is used for the dynamically updated information. The analyzed numerous existing information integrity auditing schemes together with their consequences.

scholarly journals Video Data Integrity Verification Method Based on Full Homomorphic Encryption in Cloud System

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Ruoshui Liu ◽  
Jianghui Liu ◽  
Jingjie Zhang ◽  
Moli Zhang
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Homomorphic Encryption ◽  
Data Integrity ◽  
Video Data ◽  
Verification Method ◽  
Whole Process ◽  
Integrity Checking ◽  
Verification Methods ◽  
Cloud Servers

Cloud computing is a new way of data storage, where users tend to upload video data to cloud servers without redundantly local copies. However, it keeps the data out of users' hands which would conventionally control and manage the data. Therefore, it becomes the key issue on how to ensure the integrity and reliability of the video data stored in the cloud for the provision of video streaming services to end users. This paper details the verification methods for the integrity of video data encrypted using the fully homomorphic crytosystems in the context of cloud computing. Specifically, we apply dynamic operation to video data stored in the cloud with the method of block tags, so that the integrity of the data can be successfully verified. The whole process is based on the analysis of present Remote Data Integrity Checking (RDIC) methods.

scholarly journals Fog Computing in the context of Smart Home, voice assistant and the future of IoT

2020 ◽  
Vol 21 (1) ◽  
pp. 6-12
Author(s):  
Javier Pinzón Castellanos ◽  
Miguel Antonio Cadena Carter
Keyword(s):  
Cloud Computing ◽  
Distributed Computing ◽  
Data Transmission ◽  
Smart Home ◽  
Fog Computing ◽  
Relevant Information ◽  
Raspberry Pi ◽  
Thermal Sensors ◽  
Computing Architecture ◽  
The Future

Fog Computing is the distributed computing layer that lies between the user and the cloud. A successful fog architecture reduces delay or latency and increases efficiency. This paper describes the development and implementation of a distributed computing architecture applied to an automation environment that uses Fog Computing as an intermediary with the cloud computing layer. This study used a Raspberry Pi V3 board connected to end control elements such as servomotors and relays, indicators and thermal sensors. All is controlled by an automation framework that receives orders from Siri and executes them through predetermined instructions. The cloud connection benefits from a reduced amount of data transmission, because it only receives relevant information for analysis.

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