Securing the Cloud for Big Data

2020 ◽  
pp. 1-23
Author(s):  
Michael Robinson ◽  
Kevin Jones
Keyword(s):  
Big Data ◽  
Future Research ◽  
Cloud Environment ◽  
Public Cloud ◽  
Research Areas ◽  
Significant Step ◽  
Future Research Directions ◽  
And Control ◽  
Insight Into

This chapter explores how organizations can seek to secure a public cloud environment for use in big data operations. It begins by describing the challenges that cloud customers face when moving to the cloud, and proposes that these challenges can be summarized as a loss of control and visibility into the systems and controls around data. The chapter identifies thirteen areas where visibility and control can be lost, before progressing to highlight ten solutions to help regain these losses. It is proposed that planning is the most significant step a customer can take in ensuring a secure cloud for big data. Good planning will enable customers to know their data and pursue a risk-based approach to cloud security. The chapter provides insight into future research directions, highlighting research areas which hold the potential to further empower cloud customers in the medium to long term.

scholarly journals Sustainable Supply Chain in the Era of Industry 4.0 and Big Data: A Systematic Analysis of Literature and Research

2020 ◽  
Vol 12 (10) ◽  
pp. 4108 ◽  
Author(s):  
Ricardo Chalmeta ◽  
Nestor J. Santos-deLeón
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Industry 4.0 ◽  
Future Research ◽  
Sustainable Supply Chain ◽  
Research Directions ◽  
Systematic Analysis ◽  
Different Types ◽  
Future Research Directions ◽  
Insight Into

Supply chain sustainability (SCS) in the age of Industry 4.0 and Big Data is a growing area of research. However, there are no systematic and extensive studies that classify the different types of research and examine the general trends in this area of research. This paper reviews the literature on sustainability, Big Data, Industry 4.0 and supply chain management published since 2009 and provides a thorough insight into the field by using bibliometric and network analysis techniques. A total of 87 articles published in the past 10 years were evaluated and the top contributing authors, countries, and key research topics were identified. Furthermore, the most influential works based on citations and PageRank were obtained and compared. Finally, six research categories were proposed in which scholars could be encouraged to expand Big Data and Industry 4.0 research on SCS. This paper contributes to the literature on SCS in the age of Industry 4.0 by discussing the challenges facing current research but also, more importantly, by identifying and proposing these six research categories and future research directions.

Software-Defined Networks (SDN)

2019 ◽  
pp. 516-536 ◽  
Author(s):  
Rabia Bilal ◽  
Bilal Muhammad Khan
Keyword(s):  
Programming Languages ◽  
Research Work ◽  
Future Research ◽  
Software Defined Networks ◽  
New Paradigm ◽  
Research Areas ◽  
Depth Analysis ◽  
Future Research Directions ◽  
And Control ◽  
And Storage

Software-defined networks (SDN) are a new paradigm shift in the world of network centralized command and control, providing network omniscience and separates control and data planes. Most of the research work till date focuses on increasing efficiency and manageability of computational and storage resources which results in emergence of current virtualization technologies. The feasibility and applications of SDN in current datacenters and network infrastructures is being studied by academia, industry, and the standardization bodies. This chapter explains SDN concepts and its difference from legacy networking, interrelated terminologies, protocols, programming languages, benefits, and shortcomings. Moreover, exploration of current research areas and techniques along with in-depth analysis and future research directions will be presented.

A Review of Minimum Quantity Lubrication (MQL) based on Bibliometry

2020 ◽  
Vol 13 ◽  
Author(s):  
Gaurav Gaurav ◽  
Abhay Sharma ◽  
G S Dangayach ◽  
M L Meena
Keyword(s):  
Descriptive Analysis ◽  
Minimum Quantity Lubrication ◽  
Citation Network ◽  
Machining Process ◽  
Cutting Fluid ◽  
Future Research ◽  
Research Directions ◽  
Minimum Quantity ◽  
Research Areas ◽  
Future Research Directions

Background: Minimum quantity lubrication (MQL) is one of the most promising machining techniques that can yield a reduction in consumption of cutting fluid more than 90 % while ensuring the surface quality and tool life. The significance of the MQL in machining makes it imperative to consolidate and analyse the current direction and status of research in MQL. Objective: This study aims to assess global research publication trends and hot topics in the field of MQL among machining process. The bibliometric and descriptive analysis are the tools that the investigation aims to use for the data analysis of related literature collected from Scopus databases. Methods: Various performance parameters are extracted, such as document types and languages of publication, annual scientific production, total documents, total citations, and citations per article. The top 20 of the most relevant and productive sources, authors, affiliations, countries, word cloud, and word dynamics are assessed. The graphical visualisation of the bibliometric data is presented in terms of bibliographic coupling, citation, and co-citation network. Results: The investigation reveals that the International Journal of Machine Tools and Manufacture (2611 citations, 31 hindex) is the most productive journal that publishes on MQL. The most productive institution is the University of Michigan (32 publications), the most cited country is Germany (1879 citations), and the most productive country in MQL is China (124 publications). The study shows that ‘Cryogenic Machining’, ‘Sustainable Machining’, ‘Sustainability’, ‘Nanofluid’ and ‘Titanium alloy’ are the most recent keywords and indications of the hot topics and future research directions in the MQL field. Conclusion: The analysis finds that MQL is progressing in publications and the emerging with issues that are strongly associated with the research. This study is expected to help the researchers to find the most current research areas through the author’s keywords and future research directions in MQL and thereby expand their research interests.

scholarly journals A Conceptual Framework and Propositions for the Acceptance of Mobile Services

2007 ◽  
Vol 2 (2) ◽  
pp. 61-73 ◽  
Author(s):  
Sally Rao ◽  
Indrit Troshani
Keyword(s):  
Mobile Services ◽  
User Acceptance ◽  
Future Research ◽  
Research Directions ◽  
Consumer Adoption ◽  
Business Opportunities ◽  
Managerial Implications ◽  
Lead Users ◽  
Future Research Directions ◽  
Insight Into

Mobile services are heralded to create a tremendous spectrum of business opportunities. User acceptance of these services is of paramount importance. Consequently, a deeper insight into theory-based research is required to better understand the underlying motivations that lead users to adopting mobile services. As mobile services bring additional functional dimensions, including hedonic and experiential aspects, using extant models for predicting mobile services acceptance by individuals may be inadequate. The aim of this paper is to explore, analyse and critically assess the use of existing acceptance theories in the light of the evolving and ubiquitous mobile services and their underlying technologies. Constructs affecting consumer adoption behaviour are discussed and relevant propositions are made. Managerial implications are explored and future research directions are also identified.

The 100 most-cited articles in castration-resistant prostate cancer: a bibliometric analysis

2021 ◽  
Keyword(s):  
Cancer Research ◽  
Bibliometric Analysis ◽  
Future Research ◽  
Castration Resistant Prostate Cancer ◽  
Research Areas ◽  
Castration Resistant ◽  
The Usa ◽  
Future Research Directions ◽  
Different Characteristics ◽  
Number Of Citations

Purpose: To assess the present landscape and future research directions, a bibliometric analysis was performed to identify the characteristics of the 100 most-cited articles (T100 articles) on CRPC research. Methods: A list of the T100 articles investigating CRPC was generated by searching the Web of Science (WoS) Core Collection database. Different characteristics of the T100 articles, including the countries/territories, journals, authors, and research areas, were analyzed. Results: The number of citations of T100 articles published between 1992 and 2017 ranged from 282 to 3594, with an average of 654.9 citations. According to the topic of the article, ''Mechanisms related to tumor progression or metastasis'' ranked first with 41 T100 articles, while immunotherapy ranked fourth with 7 T100 articles. The T100 articles originated from 31 countries, with more than half originating from the USA (n = 89). Professor Scher HI published the most T100 articles as the first author (4) and as the corresponding author (5), while Pro De Bono JS from the Institute of Cancer Research published 3 articles as the first author and 8 articles as the corresponding author. The journal Cancer Research published 20 T100 articles with a total of 8946 citations. The number of T100 articles(r = 0.485, P = 0.01) and the total number of citations(r = 0.626, P < 0.001) were all positively correlated with the IF of the journal. Conclusions: This analysis offers a historical perspective on the progress and attempts to reveal future trends in CRPC research using bibliometric analysis. This study's results suggest that immunotherapy and the study of androgen receptors as well as their signaling axes will possibly be hot topics and trends in CRPC research.

Security of the Cloud

2015 ◽  
pp. 363-404 ◽  
Author(s):  
Khalid Al-Begain ◽  
Michal Zak ◽  
Wael Alosaimi ◽  
Charles Turyagyenda
Keyword(s):  
Service Providers ◽  
Denial Of Service ◽  
Cloud Service ◽  
Future Research ◽  
Cloud Environment ◽  
Ddos Attacks ◽  
Security Attacks ◽  
Edos Attacks ◽  
Future Research Directions ◽  
Cloud Users

The chapter presents current security concerns in the Cloud Computing Environment. The cloud concept and operation raise many concerns for cloud users since they have no control of the arrangements made to protect the services and resources offered. Additionally, it is obvious that many of the cloud service providers will be subject to significant security attacks. Some traditional security attacks such as the Denial of Service attacks (DoS) and distributed DDoS attacks are well known, and there are several proposed solutions to mitigate their impact. However, in the cloud environment, DDoS becomes more severe and can be coupled with Economical Denial of Sustainability (EDoS) attacks. The chapter presents a general overview of cloud security, the types of vulnerabilities, and potential attacks. The chapter further presents a more detailed analysis of DDoS attacks' launch mechanisms and well-known DDoS defence mechanisms. Finally, the chapter presents a DDoS-Mitigation system and potential future research directions.

Security of the Cloud

2018 ◽  
pp. 1511-1554
Author(s):  
Khalid Al-Begain ◽  
Michal Zak ◽  
Wael Alosaimi ◽  
Charles Turyagyenda
Keyword(s):  
Service Providers ◽  
Denial Of Service ◽  
Cloud Service ◽  
Future Research ◽  
Cloud Environment ◽  
Ddos Attacks ◽  
Security Attacks ◽  
Edos Attacks ◽  
Future Research Directions ◽  
Cloud Users

The chapter presents current security concerns in the Cloud Computing Environment. The cloud concept and operation raise many concerns for cloud users since they have no control of the arrangements made to protect the services and resources offered. Additionally, it is obvious that many of the cloud service providers will be subject to significant security attacks. Some traditional security attacks such as the Denial of Service attacks (DoS) and distributed DDoS attacks are well known, and there are several proposed solutions to mitigate their impact. However, in the cloud environment, DDoS becomes more severe and can be coupled with Economical Denial of Sustainability (EDoS) attacks. The chapter presents a general overview of cloud security, the types of vulnerabilities, and potential attacks. The chapter further presents a more detailed analysis of DDoS attacks' launch mechanisms and well-known DDoS defence mechanisms. Finally, the chapter presents a DDoS-Mitigation system and potential future research directions.

Future Research Directions in E-Tourism Studies

Big Data ◽  
2016 ◽  
pp. 2368-2387
Author(s):  
Hajime Eto
Keyword(s):  
Big Data ◽  
Future Research ◽  
Research Directions ◽  
Scientific Methods ◽  
Tourism Studies ◽  
The Future ◽  
Future Research Directions ◽  
And Behaviors ◽  
Public Voice

As this book has the limited numbers of chapters and pages, many important issues remain unanalyzed. This chapter picks up and roughly discusses some of them for the future analyses in more analytical ways. The focuses are placed on how to apply the data scientific methods to the analyses of public voice, claims and behaviors of tourists, customers and the general publics by using the big data already acquired and stored somewhere.

Big Data Analytics Driven Supply Chain Transformation

2019 ◽  
pp. 106-124 ◽  
Author(s):  
Mondher Feki
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Future Research ◽  
Research Directions ◽  
Digital Platforms ◽  
New Frontier ◽  
Future Research Directions ◽  
Chain Transformation

Big data has emerged as the new frontier in supply chain management; however, few firms know how to embrace big data and capitalize on its value. The non-stop production of massive amounts of data on various digital platforms has prompted academics and practitioners to focus on the data economy. Companies must rethink how to harness big data and take full advantage of its possibilities. Big data analytics can help them in giving valuable insights. This chapter provides an overview of big data analytics use in the supply chain field and underlines its potential role in the supply chain transformation. The results show that big data analytics techniques can be categorized into three types: descriptive, predictive, and prescriptive. These techniques influence supply chain processes and create business value. This study sets out future research directions.

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