Adoption Of Cloud Computing Research Articles

Cloud-ElGamal and Fast Cloud-RSA Homomorphic Schemes for Protecting Data Confidentiality in Cloud Computing

Homomorphic encryption (HE) is an encryption form that offers a third-party with the ability to carry out computations on encrypted data. This property can be considered as a great solution to get over some obstacles limiting the wide-spread adoption of cloud computing (CC) services. Since CC environments are threatened by insider/outsider security attacks and since CC consumers often access to CC services using resource-limited devices, the HE schemes need to be promoted at security level and at running time to work effectively. For this reason, at EMENA-TSSL'16 and at WINCOM'16, the authors respectively boosted the RSA and ElGamal cryptosystems at security level, Cloud-RSA and Cloud-ElGamal. At SCAMS'17 and at EUSPN'17, the authors then suggested two fast variants of the Cloud-RSA scheme. All proposed schemes support the multiplicative homomorphism (MH) over the integers. The aim of this article is to compare the Cloud-ElGamal scheme with the Cloud-RSA schemes. This article first briefly presents the HE schemes and analyzes their security. This article then implements the schemes, compare and discuss their efficiency.

Data Provenance in the Cloud: A Blockchain-Based Approach

Ubiquitous adoption of cloud computing and virtualization technology has necessitated the need for strong security mechanisms. Multiple entities are involved in creating, exchanging, and altering data objects in the cloud environment, making it challenging to track malicious activities and security violations. To address these issues, there is a need for a data provenance framework, with which each data object in the federated cloud environment can be tracked and recorded. Although log-based provenance provides the ability to track operations conducted on digital assets, the provenance data are not transparent and immutable. Blockchain technology offers a promising mechanism for building a tamper-proof information system backed by strong cryptographic primitives. In this article, we propose BlockCloud, a blockchain-empowered data provenance architecture for the cloud computing platform. In addition, we present a proof-of-stake (PoS) consensus mechanism for BlockCloud to alleviate the overhead of computational requirements that the traditional proof-of-work (PoW) consensus needs. Finally, we discuss several research challenges and vulnerabilities that need to be addressed to realize BlockCloud.

Multiple Perspective of Cloud Computing Adoption Determinants in Higher Education a Systematic Review

Cloud computing has become a major talking point in recent times. An innovation such as cloud computing for higher education institutions (HEI) can be a cost effective means to operate their IT systems effectively without having to spend vast amounts of money on developing their IT infrastructure. HEIs also face the burden of several challenges e.g. limited infrastructure resources and IT budget, as well as limited teaching staff, technical experts, and IT skilled personnel. With support from a systematic literature review approach, this article identifies the key determinants of cloud adoption from a technological, organisational, environmental and personal perspectives. A total of 17 cloud adoption studies in the HEI context and their respected models from the period of 2012 to 2017 are reviewed and discussed. The findings suggest a lack of cloud adoption studies in the HEI domain from multiple perspectives, particularly in relation to the wider socio-technical concerns related to cloud adoption and future studies related to this research gap are deliberated.

English

English

English

The trend in information technology has been changed by cloud computing (CC) services to facilitate the day to day business activities. CC services benefits for business and information technology (IT) includes a secure platform, reducing cost and increasing productivity. There are some challenges for some organisations that adopting CC services without ensuring that the information in the cloud is secure. The primary objective of this research is to investigate the IT and IT professional perception regarding the adoption of CC services as a new generation trend in computing technology. However, the extent of CC adoption services, to identify some of the factors motivating and some challenges affecting the adoption of CC services in England. Still some organisations are struggling, how to create a secure and cost effective CC services environment.The expected finding from this research believe to provide the certain analysis and confirm the significant factors from which perceptions are derived through classification, that can address the business and technology related issues by CC services. Especially, in this study, the CC users analyse the secure platform technologies, compatibility, cost evaluation and some other types of control they assume are beneficial for the deployment of on-premise or in the cloud environment. The interview data are presented, where CC services users reviews are collected to rate the different types of important information’s related to CC services adoption. Then results are used to determine the compatibility, security and cost effectiveness are critical parameter to make this technology as a turning point for the organisation for their day to day business activities.

DETERMINANTS OF CLOUD COMPUTING ADOPTION BY ROMANIAN SMES IN THE DIGITAL ECONOMY

The purpose of this paper is to explore the process of Cloud Computing adoption within Romanian Small and Medium sized Enterprises in the digital age. Most of the scientific papers related to this topic examine the general outlook of cloud computing implementation in Romania and focus on the use of the afore-mentioned technologies by large scale companies. In order to identify the factors that have an influence over the choice of Romanian SMEs to adopt cloud computing technology, a conceptual model has been set forth. The model’s dependent variable is the choice of the company’s management to implement cloud computing technologies. Five different independent types of variable structures which have an effect on the adoption of cloud computing within SMEs were identified. The five categories of variables are competition & government, ICT providers & firm departments, employee, manager and technological factors. Each of these categories of determinants encompasses at their turn two or more constructs. An online survey tested the model based on the responses of managers and directors from 198 Romanian SMEs from the cities of Bucharest and Cluj. The validity of the model was performed by completing factor analysis and reliability tests of the data; a logistic regression analysis was deployed to test the research hypotheses. The results emphasized that the managers’ know-how on cloud computing and the perceived costs of implementing the technology represent the main components influencing the spreading of cloud computing among Romanian SMEs. This study makes a valuable contribution to the academic environment but to businesses as well. The model can be used to examine the implementation of different innovative applications. Companies which offer cloud computing services could take advantage of the outcomes of this study to expand the degree of cloud service introduction among SMEs.

Multilayered Autoscaling Performance Evaluation: Can Virtual Machines and Containers Co–Scale?

Abstract The wide adoption of cloud computing by businesses is due to several reasons, among which the elasticity of the cloud virtual infrastructure is the definite leader. Container technology allows increasing the flexibility of an application by adding another layer of virtualization. The containers can be dynamically created and terminated, and also moved from one host to another. A company can achieve a significant cost reduction and increase the manageability of its applications by allowing the running of containerized microservice applications in the cloud. Scaling for such solutions is conducted on both the virtual infrastructure layer and the container layer. Scaling on both layers needs to be synchronized so that, for example, the virtual machine is not terminated with containers still running on it. The synchronization between layers is enabled by multilayered cooperative scaling, implying that the autoscaling solution of the virtual infrastructure layers is aware of the decisions of the autoscaling solution on the container layer and vice versa. In this paper, we introduce the notion of cooperative multilayered scaling and the performance of multilayered autoscaling solutions evaluated using the approach implemented in ScaleX (previously known as Autoscaling Performance Measurement Tool, APMT). We provide the results of the experimental evaluation of multilayered autoscaling performance for the combination of virtual infrastructure autoscaling of AWS, Microsoft Azure and Google Compute Engine with pods horizontal autoscaling of Kubernetes by using ScaleX with four distinct load patterns. We also discuss the effect of the Docker container image size and its pulling policy on the scaling performance.

Usability factors predicting continuance of intention to use cloud e-learning application

In this ever-progressive digital era, conventional e-learning methods have become inadequate to handle the requirements of upgraded learning processes especially in the higher education. E-learning adopting Cloud computing is able to transform e-learning into a flexible, shareable, content-reusable, and scalable learning methodology. Despite plentiful Cloud e-learning frameworks have been proposed across literature, limited researches have been conducted to study the usability factors predicting continuance intention to use Cloud e-learning applications. In this study, five usability factors namely Computer Self Efficacy (CSE), Enjoyment (E), Perceived Ease of Use (PEU), Perceived Usefulness (PU), and User Perception (UP) have been identified for factor analysis. All the five independent variables were hypothesized to be positively associated to a dependent variable namely Continuance Intention (CI). A survey was conducted on 170 IT students in one of the private universities in Malaysia. The students were given one trimester to experience the usability of Cloud e-Learning application. As an instrument to analyse the usability factors towards continuance intention of the application, a questionnaire consisting thirty questions was formulated and used. The collected data were analysed using SMARTPLS 3.0. The results obtained from this study observed that computer self-efficacy and enjoyment as intrinsic motivations significantly predict continuance intention, while perceived ease of use, perceived usefulness and user perception were insignificant. This outcome implies that computer self-efficacy and enjoyment significantly affect the willingness of students to continue using Cloud e-learning application in their studies. The discussions and implications of this study are vital for researchers and practitioners of educational technologies in higher education.

Do strategy, processes, personnel and technology affect firm’s propensity to adopt cloud computing?

PurposePrevious empirical research on cloud computing (CC) adoption factors has examined the effects of only a small number of firm’s characteristics on CC adoption. The purpose of this paper is to investigate empirically the effects of a wide set of firm’s characteristics, which concern four important aspects of it, its strategy, processes, personnel and technology, on the propensity to adopt CC.Design/methodology/approachHaving as theoretical background the technology, organization and environment (TOE) theory of technological innovation adoption, in combination with Scott-Morton’s framework on firm’s main elements, ten research hypotheses have been developed based on previous CC and management literature. They were tested using data collected through the e-Business W@tch Survey of the European Commission from 676 European firms from three traditional manufacturing sectors.FindingsThe results reveal three characteristics of a firm that affect positively its propensity to adopt CC for all firm sizes: the adoption of ICT investment reduction strategy, the adoption of product/service innovation strategy and the sophistication of firm’s administration support ICT infrastructure. Furthermore, they reveal four additional characteristics of a firm that affect positively the propensity for CC adoption only in the small firms: the adoption of process innovation strategy, the employment of ICT personnel, as well as the sophistication of firm’s production support and e-sales ICT infrastructures.Research limitations/implicationsFirst, this study provides a theoretical foundation for the elaboration of the organizational perspective of the TOE theory of technological innovation adoption, which opens a new stream of CC adoption factors research, investigating the effects of a wide range of firm’s characteristics on CC adoption. Second, based on the above foundation, this study enriches substantially the empirical literature on CC adoption factors. The main limitation of this study is that it has been based on data from only three European manufacturing sectors.Practical implicationsThe findings provide new interesting insights concerning specific firm’s characteristics and therefore internal conditions that increase its propensity for CC adoption, and reveal specific kinds of strategy and ICT infrastructures for which CC is more appropriate and beneficial.Originality/valueThe authors have developed a theoretical foundation for extending our knowledge concerning the characteristics and internal conditions of firms that favor/promote the adoption of CC, which supports and enables the substantial extension of the existing knowledge base on CC adoption factors. Based on this theoretical foundation, the authors have formulated and tested ten research hypotheses concerning effects of firm’s strategic directions, processes, ICT infrastructures and ICT personnel, which have not been investigated previously, on CC adoption propensity.

Efficient Cloud Storage with Data Partitioning and Replication Using Advanced Encryption Standard

Cloud computing associate the computing and storage resources controlled by different operating systems to make available services such as large-scaled data storage and high performance computing to users. The benefits of low-cost, negligible management (from a user's perspective), and greater flexibility come with increased security concerns is one of the most crucial aspects among those prohibiting the wide-spread adoption of cloud computing. The data outsourced to a public cloud must need to be secured. This work gives Division and Replication of Data (DROPs) inside the Cloud for Optimal Performance and Security that judicially fragments user files into portions and replicates them at strategic places in the cloud. The division of a files into fragments is achieved based on a given consumer standards such that the individual fragments do not comprise any meaningful facts. The node separation is ensured by the means of the Grid Topology algorithm. To further improve the retrieval time, replicate fragments over the nodes that generate the highest read/write requests. The data encrypted using AES encryption algorithm. Duplication checking is implementing to provide efficient storage and time based access control for secure file access system.

Applying Catastrophe Theory for Network Anomaly Detection in Cloud Computing Traffic

In spite of the tangible advantages of cloud computing, it is still vulnerable to potential attacks and threats. In light of this, security has turned into one of the main concerns in the adoption of cloud computing. Therefore, an anomaly detection method plays an important role in providing a high protection level for network security. One of the challenges in anomaly detection, which has not been seriously considered in the literature, is applying the dynamic nature of cloud traffic in its prediction while maintaining an acceptable level of accuracy besides reducing the computational cost. On the other hand, to overcome the issue of additional training time, introducing a high-speed algorithm is essential. In this paper, a network traffic anomaly detection model grounded in Catastrophe Theory is proposed. This theory is effective in depicting sudden change processes of the network due to the dynamic nature of the cloud. Exponential Moving Average (EMA) is applied for the state variable in sliding window to better show the dynamicity of cloud network traffic. Entropy is used as one of the control variables in catastrophe theory to analyze the distribution of traffic features. Our work is compared with Wei Xiong et al.’s Catastrophe Theory and achieved a maximum improvement in the percentage of Detection Rate in week 4 Wednesday (7.83%) and a 0.31% reduction in False Positive Rate in week 5 Monday. Additional accuracy parameters are checked and the impact of sliding window size in sensitivity and specificity is considered.

The Slow HTTP Distributed Denial of Service Attack Detection in Cloud

Cloud computing became popular due to nature as it provides the flexibility to add or remove the resources on-demand basis. This also reduces the cost of investments for the enterprises significantly. The adoption of cloud computing is very high for enterprises running their online applications. The availability of online services is critical for businesses like financial services, e-commerce applications, etc. Though cloud provides availability, still these applications are having potential threats of going down due to the slow HTTP Distributed Denial of Service (DDoS) attack in the cloud. The slow HTTP attacks intention is to consume all the available server resources and make it unavailable to the real users. The slow HTTP DDoS attack comes with different formats such as slow HTTP headers attacks, slow HTTP body attacks and slow HTTP read attacks. Detecting the slow HTTP DDoS attacks in the cloud is very crucial to safeguard online cloud applications. This is a very interesting and challenging topic in DDoS as it mimics the slow network. This paper proposed a novel method to detect slow HTTP DDoS attacks in the cloud. The solution is implemented using the OpenStack cloud platform. The experiments conducted exhibits the accurate results on detecting the attacks at the early stages. The slowHTTPTest open source tool is used in this experiment to originate slow HTTP DDoS attacks.

Challenges in adoption of Cloud Computing by Companies in 2019

Challenges in adoption of Cloud Computing by Companies in 2019

A Theoretical Model for Cloud Computing Adoption Saudi Arabia For Small and Medium Size Enterprise (SMEs) in ICT Sector

A Theoretical Model for Cloud Computing Adoption Saudi Arabia For Small and Medium Size Enterprise (SMEs) in ICT Sector

English

Cloud computing (CC) is a new trend in information technology and has the potential to play a major role, in addressing inefficient resources, make a fundamental growth and competitiveness for large, small and medium enterprises (SMEs) internationally. The main benefits of adoption of CC services by Large and SMEs will be able to use the latest technology, without the need for the upfront cost, but reducing cost, providing a secure information platform and increasing productivity. The main drawback is that most organisations are adopting the CC without properly understanding that information data they are storing in the cloud is secure or not. The primary objective of this paper is to explore the CC adoption from large and SME perspective internationally. The current state of CC information intensity, different levels of external and other support in the organisations, motivations, requirements prevent the intensity of information and various level of external and other support for CC environment, the study findings can provide guidance on how to address the business and technology risks associated by CC adoption. However, a survey is conducted internationally on 107 Large and SMEs through survey monkey website, which shows interest in the CC services adoption. Specifically, in this paper users are evaluated through 6 factors, for instance, external support, competitive pressure, senior management support, employees cloud knowledge, adequate resources and information intensity.Though survey it is revealed that already adopted some cloud services are 84.11%, are in the processes of Implementing 8.41%, intend to adopt cloud services in the next 3 years 6.54% and don't intend to adopt any cloud services in near future 0.93%. The findings are expected to be beneficial for Large and SMEs in their adoption of CC services and may also be useful for service providers with respect to end-users’ concerns.

Views of Irish Farmers on Smart Farming Technologies: An Observational Study

The primary objective of this research is to find the disparity for slow adoption of Smart Farming Technologies (SFT) in Ireland. The usage of Cloud Computing technology among Irish farmers would help to find out the adoption behaviour barrier and way to enhance from the present system. The research will also help us to indicate the reasons for farmers in adopting and not adopting any technology. The research followed a mixed method where both surveys and interviews were used to collect the data from Irish farmers. A total sample of 32 farmers were selected through snowball sampling with the help of social websites. This study explored the major factors in adopting new technology among Irish farmers. It also helped to find the perception of farmers and ways to improve from the present system. The result shows that Cloud Computing adoption among the young farmers is greater while it is lower among the old farmers in Ireland.

Formulating Knowledge-Based Cloud Identity Selection

ABSTRACT Cloud identity is critical in the adoption of cloud computing. Identity providers provide identity as a service for the cloud customers to facilitate the access to resources, but often provide no informed choice of the supply arrangements. The cloud customer requires a say in the elements of service that impact their expectations and quality of service – particularly in relation to the security and privacy of information. In this paper, we provide a novel software solution for addressing the problem. It allows for selecting a most trustable provider, in terms of security, privacy, risk, and standards. The application architecture uses a trust evaluation model as a third-party agency for informing the service user of evidence for and against a choice. A case study and application build demonstrate the feasibility and usefulness of the proposed method in a real cloud environment.

Towards Development of an Integrated Cloud-Computing Adoption Framework — A Case of Indian School Education System

Many theoretical models viz., technology acceptance model (TAM), technology–organization–environment (TOE), diffusion of innovation (DOI), and human–organization–technology-fit (HOT-fit), etc., have been developed, validated, and tested to explain the acceptance of innovative technologies by the intended end users. However, given the limitations associated with these theoretical models as well as different cloud computing adoption scenario, they may not point out to the major constructs and the variables under so-called “selective contexts” in an explicit manner. Therefore, several research studies have been undertaken to integrate more than one model to provide a holistic evaluation of the determinants of cloud computing adoption for different domains. Such studies have also been conducted for education sector as well. But, the target of these studies is mostly specific to higher education using TOE or TAM models. To solve this limitation, we propose integrated approach of TAM, TOE framework, DOI, and HOT-fit frameworks in an effort to improve predictive power of proposed resulting model and, stretching the constructs to enrich the literature and implementing the same for Indian school education system as a case study.

Factors Affecting Students' Intention Toward Mobile Cloud Computing

The adoption of mobile cloud computing (MCC) in education systems still faces several obstacles due to technical, environmental, psychological, and individual issues. Considering numerous advantages associated with the adoption of MCC, this article evaluates the frequency of using MCC by students at King Abdul-Aziz University (KAU) and investigates the factors that influence student intention to use MCC. A survey approach has been used to include 163 students of KAU through a random sampling. Results showed that the attitude towards MCC, perceived ease of use, perceived usefulness, social influence, accessibility of technology, individual characteristics, perceived privacy, and security are all important determinants of intention to use MCC. Findings contribute towards research and practice by revealing crucial factors that impact student intention to adopt mobile cloud computing in developing countries.

Adoption of Cloud Computing in BFSI Industry

Adoption of Cloud Computing in BFSI Industry