Adoption Of Cloud Computing Research Articles

A Model for Adoption of Open-Source Cloud Computing: Platform as a Service and Software as a Service

A Model for Adoption of Open-Source Cloud Computing: Platform as a Service and Software as a Service

Towards an Understanding of Cloud Computing Adoption in SMEs

The advent of digital technologies such as cloud computing has provided enormous opportunities for small and medium-sized enterprises (SMEs) to digitalise their businesses. However, with increasing cloud computing adoption, the security and privacy threats to the SMEs are on the rise. By conducting an extensive review of literature, this paper examines and identifies the security factors that influence cloud computing adoption specifically by SMEs. The literature review focused on papers published in ten years related to the security requirements and associated cloud computing adoption factors by SMEs. The framework focused on understanding socio-technical factors that influence the intent to adopt cloud computing by SMEs. The findings attest to the impacts of key security and privacy-related factors (including cloud security standard, data privacy concerns, data security concerns, skilled personnel, technology readiness, perceived cloud security benefits, legal compliance and trust in cloud service providers) on SMEs' intent to adopt cloud computing.

Deep Learning Applications in Cloud Security: Challenges and Opportunities

The rapid adoption of cloud computing has transformed the digital landscape, offering unparalleled flexibility, scalability, and cost-efficiency. However, this evolution has also introduced significant security challenges, making cloud environments attractive targets for cyber threats. Deep learning, a subset of artificial intelligence, presents innovative solutions to enhance cloud security. This paper explores the applications of deep learning in cloud security, focusing on its ability to detect and mitigate threats in real-time, automate security protocols, and improve anomaly detection. We analyze various deep learning models and techniques employed in cloud security, such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and autoencoders. The paper also discusses the challenges associated with integrating deep learning into cloud security, including data privacy concerns, computational costs, and the need for large datasets. Furthermore, we highlight the opportunities deep learning provides in creating more resilient cloud infrastructures, including advancements in threat intelligence and proactive security measures. By examining current research and practical implementations, this paper aims to provide a comprehensive overview of the state-of-the-art in deep learning applications in cloud security and outline future directions for research and development.

The Impact of Cloud Computing in Promoting Economic Growth through SMEs in the United States

Cloud Computing, being one of the most recent innovative developments of the IT world, has been instrumental not just to the success of SMEs but, through their productivity and innovative contribution to the economy, has even made a remarkable contribution to the economic growth of the United States. To this end, the study focuses on how cloud computing technology has impacted economic growth through SMEs in the United States. Relevant literature connected to the variables of interest in this study was reviewed, and secondary data was generated and utilized in the analysis section of this paper. The findings of this paper revealed that there have been meaningful contributions that the usage of virtualization has made in the commercial dealings of small firms in the United States, and this has also been reflected in the economic growth of the country. This paper further revealed that as important as cloud-based software is, some SMEs are still skeptical about how it can help improve their business and increase their bottom line and hence have failed to adopt it. Apart from the SMEs, some notable large firms in different industries, including information and educational services, have adopted cloud computing technology and hence contributed to the economic growth of the United States. Lastly, findings from our inferential statistics revealed that no discernible change has occurred in innovation between small and big businesses in the adoption of cloud computing. Both categories of businesses adopt cloud computing in the same way, and their contribution to the American economy has no significant difference in the usage of virtualization.

Risk Classes of Cloud Computing Project in Healthcare: A Review of Technical Report and Standards

Cloud computing has been shown to have positive impacts on the organization such as “cost savings”, “enhanced efficiency”, etc. Cloud computing has been implemented in multiple sectors around the world including the healthcare sector. The rise of chronic illnesses requires the assistance of new technologies such as cloud computing to bring flexibility and convenience to treat these illnesses. However, as with all IT architecture projects, there are risks and challenges to adopting cloud computing. As such this study aims to find the prevailing risk classes of cloud computing projects in healthcare through risk classes discussed in technical reports and standards. This study will employ TLR as a method for this study. Through this study, we found five technical reports and standards that discuss the risk management of cloud computing. The result shows that there are 13 prevalent risk classes of cloud computing. We hope that the results discovered through this study can help academics, researchers, and practitioners to recognize what are the prevalent risk classes currently discussed regarding cloud computing and whether the discussion has matured or not.

Factors Influencing the Integration of Cloud Computing in Modern Accounting Practices in the Malaysian Accounting Sector: A Conceptual Study

In the dynamic landscape of contemporary business, cloud computing has become a prevalent tool for organizations to manage and store data efficiently as more organizations adopt cloud-based solutions for their IT needs. In this case, the adoption of cloud computing is beneficial not only for managing and storing data but also for implementing effective cloud accounting systems. However, amidst the transformation and benefits, adopting and integrating cloud computing in accounting practices are not without challenges. This study aims to delve deeper into these issues to investigate the key factors influencing the adoption of cloud computing in accounting, particularly in the Malaysian business landscape. The factors explore the distinctive benefits like security, cost-effectiveness and flexibility while also shedding light on the associated challenges, with a particular emphasis on security. Despite these challenges, such as security vulnerabilities, cost overruns and potential for data loss, the study asserts that the benefits of integrating cloud computing into accounting practices substantially outweigh the hurdles. Consequently, it recommends strategic steps to ensure a smooth transition to cloud-based accounting systems. These measures are critical in aiding businesses in navigating through the challenges while capitalizing on the transformative potential of cloud computing, thereby staying competitive and agile in the rapidly evolving digital era.

Sustainability in small and medium enterprises: A circular economy approach using cloud computing

AbstractSustainable production and consumption are the need of the hour. Adopting the Circular Economy (CE) approach fosters sustainable business practices. Cloud computing is a new way of storage and application deployment. Cloud computing enables sustainable business processes, which in turn contributes towards the effective implementation of the Circular Approach to Business Practices (CABP). The current study aims to understand the potential of cloud computing to foster circular economy practices in Small and Medium Enterprises (SMEs). We conducted a Systematic review of 186 scholarly articles published in Web of Science (WOS), selected using the PRISMA framework. We conducted scientometric analysis on sources, authors and country level and thematic analysis to pinpoint further research areas. This was followed by a detailed literature review of the articles selected to study the concept and current practices of circular economy and an evaluation of its implementation in emerging economies. The paper proposes an integrated framework grounded in two approaches, that is, the Technology, Organization and Environment (TOE) framework and institutional isomorphism as determinants of cloud adoption and CE implementation. The proposed model explores the impact of institutional forces on the various parameters of TOE, thereby culminating in the adoption of Cloud Computing in SMEs. The study would encourage leaders and managers of SMEs to adopt cloud computing for competitive advantage and achieve a circular economy approach together. The adoption of cloud‐based applications has a great potential to foster industrial and economic progress with minimum damage to the ecosystem, furthering sustainability and achieving Sustainable Development Goals (SDGs).

Factors and Barriers to Cloud Computing Adoption for Small and Medium-Sized Enterprises in Kuwait

Factors and Barriers to Cloud Computing Adoption for Small and Medium-Sized Enterprises in Kuwait

A Proposed Framework of VAPT Services in Web Application Deployed on Infrastructure as a Service (Iaas)

Most companies in Malaysia require their employees to work from home due to the COVID-19 pandemic. This situation also increased the number of data generated from various sources, thus exposing them to different security risks. Even though the employees are encouraged to work from home because of the COVID-19 pandemic, they still need to communicate among themselves to do their work. However, working from home depends mainly on cloud computing (CC) applications that help employees accomplish their daily work efficiently. Injection attacks, such as SQL injection and Cross-Site Scripting (XSS), are critical security vulnerabilities that can lead to unauthorized access, data breaches, and potential service disruptions in web applications. With the increasing adoption of cloud computing, web applications deployed on cloud platforms like Amazon Web Services (AWS) are becoming more prevalent and vulnerable to such attacks. Therefore, it is crucial to develop practical Vulnerability Assessment and Penetration Testing (VAPT) techniques specifically tailored to identify and detect injection vulnerabilities in web applications deployed on AWS. However, existing VAPT methodologies often need more comprehensive coverage for injection vulnerabilities in cloud-based web applications, and they may not consider the unique characteristics and challenges associated with the AWS environment. This research addresses this gap by proposing an enhanced VAPT framework focusing specifically on injection attacks in web applications deployed on AWS.

Comparison of Three Resouces Allocation Technique in Cloud Computing

The shift to the cloud enables organizations of all sizes to swiftly, efficiently, and innovatively move their operations. The adoption of cloud computing has significantly transformed most organizations' work, communication, and collaboration methods, making it a crucial necessity for maintaining competitiveness in the digital age. Organizations are implementing cloud bursting to handle IT demand peaks by utilizing private cloud capacity and public cloud capacity, freeing up local resources for critical applications, and reverting data back to the private cloud. Organizations face challenges in allocating resources in cloud computing to automatically switch from private cloud to public cloud, leading to system issues, user frustration, operational failure, increased stress, and revenue loss. To address these concerns. This paper investigates traffic predictions by comparing three prediction tools, such as support vector machines, spatio-temporal, and edge-cloud collaborative schemes, and proposing conceptual solutions. Efficient cloud computing traffic management can prevent system bottlenecks, especially during peak periods, potentially leading to dissatisfied clients.

Huawei Pakistan Providing Cloud Solutions for Banking Industry: A Data Driven Study

This report explores how Huawei Pakistan's cloud solutions have revolutionized the country's banking industry. Using a combination of surveys and interviews, the study uses a mixed-methods approach to thoroughly evaluate the many effects of cloud adoption. The results are solid and highlight the significant advantages that cloud technology have provided to Pakistani banks. One major gainer is operational efficiency, with banks reporting notable increases in cost savings, process simplification, and overall operational efficiency. These results support the focus on cloud solutions' transformative potential found in the research currently in publication. Adoption of cloud computing has an equally significant impact on customer experience and satisfaction, with increased customer satisfaction levels, response times, and service innovation resulting from its use. The research findings are consistent with the literature's claim that cloud computing enables banks to offer improved customer experiences in a time when customers expect quick and easy access to services. Most importantly, the study emphasizes how crucial it is to comply with regulations and maintain data security while adopting cloud computing. After using Huawei's cloud solutions, banks in Pakistan reported a considerable improvement in data security, privacy safeguards, and regulatory compliance. In the modern banking context, the benefits of strategically using technology to pursue excellence are visible in operational efficiency, customer satisfaction, data security, and regulatory compliance. These effects are truly revolutionary. Because of the cloud's revolutionary ability, Pakistan's banking sector is well-positioned to thrive as the digital era unfolds. Currently Pakistan SBP have released the cloud adoption frame, suggest and guide how financial institution adopt cloud, and new digital banks also requiring cloud environment to support business raise rapidly. However, the cloud on the market or have less function, or have data sovereign risk. Huawei product HCS is the kind of cloud infrastructure can both provide plenty cloud services and protect data security.

THE DIGITAL TRANSFORMATION OF SMES: A COMPARATIVE REVIEW BETWEEN THE USA AND AFRICA

The digital transformation of Small and Medium-sized Enterprises (SMEs) is a critical phenomenon shaping the global business landscape. This paper presents a comparative review between the United States and Africa, exploring the diverse trajectories of digitalization within these regions. While the USA is often at the forefront of technological advancements, Africa's SMEs exhibit unique challenges and opportunities in their digital transformation journey. In the United States, SMEs have embraced digital technologies to enhance operational efficiency, improve customer experiences, and gain a competitive edge. The adoption of cloud computing, data analytics, and e-commerce platforms has become ubiquitous, fostering innovation and scalability. This comparative study delves into the specific strategies employed by American SMEs to navigate the complexities of the digital era. On the contrary, African SMEs face distinct hurdles in their digital transformation efforts. Infrastructure limitations, limited access to capital, and a diverse economic landscape present unique challenges. However, this review sheds light on the innovative approaches taken by African SMEs to overcome these barriers. Leveraging mobile technology, localized digital solutions, and collaborative networks, African SMEs are carving out their digital paths. Moreover, this comparative review emphasizes the role of government policies and support mechanisms in shaping the digital transformation landscape for SMEs in both regions. By examining regulatory frameworks, funding initiatives, and skill development programs, this paper provides a comprehensive analysis of the ecosystem supporting SMEs in their digital evolution. The digital transformation of SMEs is a dynamic process with distinct nuances in the USA and Africa. While American SMEs benefit from advanced technological infrastructures, African SMEs showcase resilience and adaptability in leveraging digital tools to overcome challenges. Understanding these diverse trajectories is essential for policymakers, businesses, and researchers seeking to foster inclusive and sustainable digital growth globally.
 Keywords: Digital Transformation, SMEs, USA, Africa, Review.

Exploring the Cloud Storage Service Adoption Through the Dual Perspectives: Protection Motivation Theory (PMT) and the Extended Unified Theory of Technology Acceptance Model (UTAUT2)

Cloud computing is spreading rapidly, but little research has been conducted to understand the effects of the protective perspective on acceptance by individuals. The goal of this study was to explore the impact of protective behavior on individuals’ adoption of cloud computing. Specifically, the study will concentrate on personal cloud storage service (CSS), widely recognized as a protective technology. Our theoretical framework endeavored to combine protection motivation theory with the extended unified theory of acceptance and use of technology and focused on the effect of threat in the context of CSS. This study tested two proposed models (Model A, Model B) by structural equation modeling using data from 392 individuals. Data were collected for people in voluntary CSS-usage settings through an online survey. Model A and model B explained 61.0% and 60.4% of the variance in the behavioral intention to accept CSS, respectively. Results showed that CSS adoption is a protective measure against data loss and identified that threat influence CSS adoption. Threat elements directly do not influence behavioral intention to adopt CSS. Threat elements mostly acted as antecedents of independent variables; perceived severity and perceived vulnerability directly influenced technology attributes (performance expectancy, effort expectancy), and showed slightly different results in contextual attributes (facilitating conditions, social influence) and consumer attributes (hedonic motivation, habits). Our study offers a unique perspective for researchers and professionals in understanding the impact of threat factors on information technology domains where protective technologies are operated. Thus, we recommend that academics and business practitioners in the realm of cloud computing should consider user’s protective motivation view of adopting CSS when designing, developing, delivering and spreading it.

Agnostic Energy Consumption Models for Heterogeneous GPUs in Cloud Computing

The adoption of cloud computing has grown significantly among individuals and in organizations. According to this growth, Cloud Service Providers have continuously expanded and updated cloud-computing infrastructures, which have become more heterogeneous. Managing these heterogeneous resources in cloud infrastructures while ensuring Quality of Service (QoS) and minimizing energy consumption is a prominent challenge. Therefore, unifying energy consumption models to deal with heterogeneous cloud environments is essential in order to efficiently manage these resources. This paper deeply analyzes factors affecting power consumption and employs these factors to develop power models. Because of the strong correlation between power consumption and energy consumption, the influencing factors on power consumption, with the addition of other factors, are considered when developing energy consumption models to enhance the treatment in heterogeneous infrastructures in cloud computing. These models have been developed for two Virtual Machines (VMs) containing heterogeneous Graphics Processing Units (GPUs) architectures with different features and capabilities. Experiments evaluate the models through a cloud testbed between the actual and predicted values produced by the models. Deep Neural Network (DNN) power models are validated with shallow neural networks using performance counters as inputs. Then, the results are significantly enhanced by 8% when using hybrid inputs (performance counters, GPU and memory utilization). Moreover, a DNN energy-agnostic model to abstract the complexity of heterogeneous GPU architectures is presented for the two VMs. A comparison between the standard and agnostic energy models containing common inputs is conducted in each VM. Agnostic energy models with common inputs for both VMs show a slight enhancement in accuracy with input reduction.

BopSkyline: Boosting privacy-preserving skyline query service in the cloud

With the widespread adoption of cloud computing, there has been great popularity of storing and querying databases in the cloud. However, such service outsourcing also entails critical data privacy concerns, as the cloud providers are generally not in the same trust domain as the data owners/users and could even suffer from data breaches. In this paper, different from most existing works that propose security designs for keyword search, we focus on secure realizations of advanced skyline query processing, which plays an important role in multi-criteria decision support applications. We propose BopSkyline, a new system framework for privacy-preserving skyline query service in cloud computing. BopSkyline is designed to not only ensure the confidentiality of outsourced databases, skyline queries, and query results, but also conceal data patterns (like the dominance relationships among database tuples) and search access patterns that may indirectly lead to data leakages. Notably, through a delicate synergy of key ideas on secure database shuffling and differentially private database padding, BopSkyline achieves a significant performance boost over the state-of-the-art. Extensive experiments demonstrate that compared with the state-of-the-art prior work, BopSkyline is up to 4.7× better in query latency and achieves up to 99.38% cost savings in communication.

The Impact of Cloud Computing Adoption on Firm Performance Among SMEs in Palestine

This study seeks to identify the driving factors of cloud computing adoption (CCA) among SMEs, and examines the extent to which CCA shape SME performance. Data was gathered from 212 Halal SMEs in Palestine. This study uses a two-phase investigative method to test the research model through integrating structural equation modeling (SEM) and machine learning. SEM findings show that perceived benefit, facilitating states, server location, perceived cost, upper management support, perceived quality, and cloud providers' support significantly affect CCA. Besides, the article verifies that CCA positively shapes SMEs' performance. Machine learning findings unravel perceived benefit as the strongest determinant of CCA. This study is an initial attempt to develop a conceptual framework that hypothesizes the links between technological-organizational-environmental (TOE) factors and SMEs' intent for CCA in Palestine and provides empirical evidence regarding these links.

Deep self-taught learning framework for intrusion detection in cloud computing environment

<p>Cloud has become a target-rich environment for malicious attacks by cyber intruders. Security is a major concern and remains an obstacle to the adoption of cloud computing. The intrusion detection system (IDS) is regarded as defense-in-depth. Unfortunately, most machine learning approaches designed for cloud intrusion detection require large amounts of labeled attack samples, but in real practice, they are limited. Therefore, the key impetus of this work is to introduce self-taught learning (STL) combining stacked sparse autoencoder (SSAE) with long short-term memory (LSTM) as a candidate solution to learn the robust feature representation and efficiently improve the performance of IDS with respect to false alarm rate (FAR) and detection rate (DR). Accordingly, the proposed approach as a first step employs SSAE to achieve dimensional reduction by learning the discriminative features from network traffic. The approach adopts LSTM to recognize the intrusion with the features encoded by SSAE. To evaluate the detective performance of our model, a comprehensive set of experiments are conducted on NSL-KDD. Also, ablation experiments are conducted to show the contribution of each component of our approach. Further, the comparative analysis shows the efficacy of our approach against the existing approaches with an accuracy of 86.31%.</p>

Exploring Strategic Decision-Making Process In Hybrid Cloud Computing Adoption Among Small And Medium-Sized Enterprises

This study delves into the strategic decision-making process concerning the adoption of hybrid cloud computing among Small and Medium-Sized Enterprises (SMEs) within the context of Bahrain. With the proliferation of digital transformation and the evolving landscape of technological infrastructure, the adoption of hybrid cloud solutions presents a compelling avenue for SMEs to enhance operational efficiency and competitive advantage. This research employs a qualitative approach, engaging in-depth interviews with 11 key stakeholders from diverse SMEs across Bahrain. Through thematic analysis, this study elucidates the multifaceted dimensions of the strategic decision-making process, encompassing factors influencing adoption, perceived benefits, challenges encountered, and the integration of hybrid cloud computing within the broader organizational strategy. The findings shed light on the considerations, including technological, organizational, regulatory, and socio-cultural aspects, shaping the adoption landscape of hybrid cloud solutions among SMEs in Bahrain.

Small and Medium Enterprises (SMEs): Key Factors Affecting the Adoption of Cloud Computing

Cloud computing is a widely recognized innovative technology that has influenced various organizations including SMEs. It has emerged as one of the most debated themes among industrialists and technocrats worldwide to keep them abreast in the competitive environment. This research employs a comprehensive literature review to analyze research theories and frameworks, data collection methods, cloud-based services, and especially key adoption determinants of cloud computing services by SMEs. By analyzing the TOE framework this study has found a strong bond among the three elements that are technological, organizational, and environmental of this framework. The key determinants that played a major role in the adoption of cloud computing services by SMEs were: relative advantage, top management support, technical readiness, and competitive pressure.

A Secure Face Verification Scheme Based on Fully Homomorphic Encryption with Anonymity

With the widespread adoption of cloud computing, the face verification process often requires the client to upload the face to an untrusted cloud server to obtain the verification results. Privacy leakage issues may arise if the client’s private information is not protected. This paper proposes a secure and anonymous face verification scheme using fully homomorphic encryption technology and SealPIR. Our scheme is a three-party solution that requires a third-party server trusted by the client. This scheme not only prevents the client’s facial data from being obtained by untrusted data servers but also prevents the data server from learning the index corresponding to the face that the client wants to verify. In a single-face verification process, the client only needs to perform one upload operation and one download operation, with a communication volume of 264 KB. We can complete a privacy-protected anonymous face verification process in 84.91 ms.