On the Adoption of Emerging Technologies in Securing and Confidentializing the Healthcare Medical Data: Survey Study (original) (raw)

A Systematic Review of Security Mechanisms for Big Data in Health and New Alternatives for Hospitals

Wireless Communications and Mobile Computing

Computer security is something that brings to mind the greatest developers and companies who wish to protect their data. Major steps forward are being taken via advances made in the security of technology. The main purpose of this paper is to provide a view of different mechanisms and algorithms used to ensure big data security and to theoretically put forward an improvement in the health-based environment using a proposed model as reference. A search was conducted for information from scientific databases as Google Scholar, IEEE Xplore, Science Direct, Web of Science, and Scopus to find information related to security in big data. The search criteria used were “big data”, “health”, “cloud”, and “security”, with dates being confined to the period from 2008 to the present time. After analyzing the different solutions, two security alternatives are proposed combining different techniques analyzed in the state of the art, with a view to providing existing information on the big data ov...

Big Data Security Issues and Challenges in Healthcare

2019

This paper embodies the usage of Big Data in Healthcare. It is important to note that big data in terms of Architecture and implementation might be or has already or will continue to assist the continuous growth in the field of healthcare. The main important aspects of this study are the general importance of big data in healthcare, the positives big data will help tackle and enhance in this field and not to also forget to mention the tremendous downside big data has on healthcare that is still needed to improve or putting extensive research on. We believe there is still a long way in which institutions and individuals understand the hidden truth about big data. We have highlighted the various ways one could be confidently relied on big data and on the other hand highlighted the weighted importance of big problem big data and expected solutions.

A survey on techniques, methods and security approaches in big data healthcare

Zenodo (CERN European Organization for Nuclear Research), 2023

A huge percentage of people especially in developed countries spend a good chunk of their wealth in managing their health conditions. In order to adequately administer healthcare, governments and various organizations have embraced advanced technology for automating the health industry. In recent past, electronic health records have largely been managed by Enterprise Resource Planning and legacy systems. Big data framework steadily emerge as the underlying technology in healthcare, which offers solutions that limits capacity of others systems in terms of storage and reporting. Automation through cloud services supported by storage of structured and unstructured health data in heterogeneous environment has improved service delivery, efficiency, medication, diagnosis, reporting and storage in healthcare. The argument support the idea that big data healthcare still face information security concern, for instance patient image sharing, authentication of patient, botnet, correlation attacks, man-in-the-middle, Distributed Denial of Service (DDoS), blockchain payment gateway, time complexities of algorithms, despite numerous studies conducted by scholars in security management for big data in smart healthcare. Some security technique include digital image encryption, steganography, biometrics, rule-based policy, prescriptive analysis, blockchain contact tracing, cloud security, MapReduce, machine-learning algorithms, anonymizations among others. However, most of these security solutions and analysis performed on structured and semi-structured data as opposed to unstructured data. This may affect the output of medical reporting of patients' condition particularly on wearable devices and other examinations such as computerized tomography (CT) Scans among others. A major concern is how to identify inherent security vulnerabilities in big healthcare, which generate images for transmission and storage. Therefore, this paper conducted a comparative survey of solutions that specifically safeguards structured and unstructured data using systems that run on big data frameworks. The literature highlights several security advancements in cryptography, machine learning, anonymization and protocols. Most of these security frameworks lacks implementation evidence. A number of studies did not provide comprehensive performance metrics (accuracy, error, recall, precision) of the models besides using a single algorithm without validated justification. Therefore, a critique on the contribution, performance and areas of improvements discussed and summarized in the paper.

Big healthcare data: preserving security and privacy

Journal of Big Data

Change is the new norm for the global healthcare sector. In fact, digitization of health and patient data is undergoing a dramatic and fundamental shift in the clinical, operating and business models and generally in the world of economy for the foreseeable future. This shift is being spurred by aging populations and lifestyle changes; the proliferation of software applications and mobile devices; innovative treatments; heightened focus on care quality and value; and evidence-based medicine as opposed to subjective clinical decisions-all of which are leading to offer significant opportunities for supporting clinical decision, improving healthcare delivery, management and policy making, surveilling disease, monitoring adverse events, and optimizing treatment for diseases affecting multiple organ systems [1, 2]. As noted above, big data analytics in healthcare carries many benefits, promises and presents great potential for transforming healthcare, yet it raises manifold barriers and challenges. Indeed, the concerns over the big healthcare data security and privacy are increased year-by-year. Additionally, healthcare organizations found that a reactive,

Security Challenges of Big Data Implementation in Health Care Systems

As technological improvement in data management techniques, Big Data tend to handle much more volumes of data. There might be higher beneficial in managing data , on the other side there is a possibility of having much more challenges in providing security for that data from the intruders. The main aim of this paper is to convey how big data works in the health care system and security related challenges in the implementation. This paper may be helpful to the researchers to find the challenges in the big data and it also gives way to find the solution for that security issues. Recent advances in rapid growing technology a huge amount of data has been generated and stored in databases, there may be a presence of various issues and challenges in Big data environment. Big data a term denotes large volume of data that can be stored, analyzed to obtain the required output. The major challenges in big data are The main characteristics of big data are volume, velocity, variety. Big data architecture for capturing the data from various data streams as well as analytic process is represented in fig 1. The data streams from various sources are obtained. They are tend to store on data storage infrastructure where it can be structured or unstructured and analytic process are done according to the privileged rights assigned to particular users (such as Data owners, technical analyst , business analyst). II. CHALLENGES IN BIG DATA The various challenges in big data are as follows [4]. They are  Distributed frameworks are those in which huge data processing are paralyzed and establish a communication across various systems  Non-relational data stores in that retrieval of data is little tedious to implement a privacy related features  Storage in which volume of data can be exploded frequently.  Endpoints are those which need to validate the authentication process.

Big and open data privacy risks in health sector: developing a trend or establishing the future?

The amount of medical data is growing rapidly in the current technological and social environment. Big data analytics are considered a highly powerful tool in assisting health service providers, researchers and patients to accelerate scientific discovery, enabling personalized medicine and improving the quality of healthcare. It is being underpinned that in order to achieve these objectives an open data strategy should be followed by public authorities allowing third parties to access medical data. This process though raises severe concerns over privacy issues relating to the use of medical information by both private and public entities. European Union trying to modernise its approach concerning personal data in general has introduced a proposal for a General Data Protection Regulation that specifically refers to and regulates health related information by introducing an enriched right to consent and the right to be forgotten. This paper conglomerates the privacy problems arising from the emergence of big data sets in medical sector as they are depicted in literature, and tries to examine to what extent the proposed Data Protection Regulation can address these issues so as to create a modern and updated legal framework by introducing new rules that will provide greater legal certainty, enhance citizens' trust in the use of their medical data, and ultimately achieve the goal of delivering efficient health services.

Potentiality of big data in the medical sector: focus on how to reshape the healthcare system

Healthcare informatics research, 2013

The main purpose of this study was to explore whether the use of big data can effectively reduce healthcare concerns, such as the selection of appropriate treatment paths, improvement of healthcare systems, and so on. By providing an overview of the current state of big data applications in the healthcare environment, this study has explored the current challenges that governments and healthcare stakeholders are facing as well as the opportunities presented by big data. Insightful consideration of the current state of big data applications could help follower countries or healthcare stakeholders in their plans for deploying big data to resolve healthcare issues. The advantage for such follower countries and healthcare stakeholders is that they can possibly leapfrog the leaders' big data applications by conducting a careful analysis of the leaders' successes and failures and exploiting the expected future opportunities in mobile services. First, all big data projects undertak...

Big data in healthcare: a discussion on the big challenges

Health and Technology, 2016

Our century has been described as the electronic age and every day new technologies or applications, that generate data with exponential rates, are emerged. As a consequence, all and more organizations are facing the problem of managing large amounts of data. Generally, the large amount of data and their handling, storage and analysis is referred as Big Data. The emerging field of Big Data poses many challenges for healthcare organizations, as healthcare data and information increases. The paper describes the emerging era of Big Data in the field of health care and focuses on their benefits, challenges and ethics providing a broad overview for healthcare researchers, practitioners and health policy makers. Furthermore, we proposed a three-dimensional model for assessing Big Data concerns in the medical context. The paper is not intended to be a comprehensive review of the state-of-the-art of Big Data technology, but rather to raise the awareness of the considerations that healthcare professionals may face or will face in the near future.

Importance of Big Data In Healthcare System A Survey Approach

International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2020

‘Big data’ is massive amounts of information that can work wonders. It has become a topic of special interest for the past two decades because of a great potential that is hidden in it. Various public and private sector industries generate, store, and analyze big data with an aim to improve the services they provide. In the healthcare industry, various sources for big data include hospital records, medical records of patients, and results of medical examinations, and devices that are a part of internet of things. Biomedical research also generates a significant portion of big data relevant to public healthcare. This data requires proper management and analysis in order to derive meaningful information. Otherwise, seeking solution by analyzing big data quickly becomes comparable to finding a needle in the haystack. There are various challenges associated with each step of handling big data which can only be surpassed by using high-end computing solutions for big data analysis. That is why, to provide relevant solutions for improving public health, healthcare providers are required to be fully equipped with appropriate infrastructure to systematically generate and analyze big data. An efficient management, analysis, and interpretation of big data can change the game by opening new avenues for modern healthcare. That is exactly why various industries, including the healthcare industry, are taking vigorous steps to convert this potential into better services and financial advantages. With a strong integration of biomedical and healthcare data, modern healthcare organizations can possibly revolutionize the medical therapies and personalized medicine.

APPLICATIONS AND CHALLENGES IN HEALTHCARE BIG DATA

International Journal of Information Technology, 2023

The manuscript's subject matter is the significant impact of big data analytics on healthcare. This emerging technology has the potential to revolutionize medical care by utilizing predictive analytics, genomics, patient profiling and healthcare administration for improved patient outcomes. This extensive research emphasizes the advantages of big data in healthcare and delves into the difficulties that come with its incorporation. The study thoroughly explores different hindrances that must be overcome when implementing big data in healthcare, such as worries related to the security and privacy of data, difficulties with interoperability, scarcity of skilled workers, expensive integration costs, and obstacles posed by regulations.