Cloud Service Model Research Articles

Literature Review on Cloud Computing: A Paradigm Combining Service-Oriented Architecture with Internet-Based Solutions

Cloud computing, a paradigm combining service-oriented architecture with Internet-based network solutions, has rapidly transformed the IT industry by offering on-demand access to shared resources. Key models of cloud services include Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). These models provide cost-effective, scalable, and flexible alternatives to traditional IT infrastructure, enabling enterprises to outsource hardware, software, and network services. Cloud systems such as Amazon EC2, Google App Engine, and IBM’s Blue Cloud illustrate these benefits, significantly lowering costs through pay-as-you-go pricing structures. However, data security and privacy have become critical concerns, as cloud users must entrust sensitive information to third-party providers. Ensuring data confidentiality and implementing fine-grained access control are essential to maintaining user trust and enabling compliance with legal and organizational regulations. The success of cloud computing in the future depends on overcoming these security challenges, allowing enterprises to fully embrace its potential

Do not get lost in the cloud: how EU financial institutions could avoid problems with cloud services arising under DORA

ABSTRACT Financial institutions turn to cloud services and entrust cloud providers with increasingly important tasks. The relationship between these two groups has largely existed outside regulatory parameters, but Digital Operational Resilience Act (DORA) is set to change that dynamic when it becomes applicable in 2025. This paper tackles two issues in this context. Firstly, it identifies the legal and practical challenges that EU financial institutions may encounter while adopting and utilising cloud services under the DORA regime. Challenges during the adoption stage include the selection of providers, decisions regarding the transfer of critical or important functions, and the choice of contractual clauses. In the usage stage, data security and financial stability emerge as the most critical concerns. One overarching difficulty is concentration risk. Secondly, the question of how to address these issues arises. Fortunately, identified challenges can be mitigated if financial institutions choose appropriate cloud deployment and service models.

Cloud Computing and Its Mechanisms: A Comprehensive Study

Abstract: Cloud computing has emerged as a transformative technology, revolutionizing how computational resources are accessed and managed. This paper explores the fundamental concepts of cloud computing, its architecture, service models, deployment models, and key mechanisms that enable its functionality. We also examine the benefits and challenges associated with cloud computing, along with its applications across various domains. The paper concludes with a discussion on future trends and potential developments in cloud computing.

Multi-Tenant IaaS Cloud Security Evaluation Model

Tenants that rent computer resources to run sophisticated systems might benefit from increased resource flexibility provided by the infrastructure cloud (IaaS) service model. The user will thus be launched into virtual computers after completing the authentication procedure, where they will start the upload process to the cloud.Secure data access is offered by suggested system's implementation of virtual machines and key management.Session management and failed authentication are other key components of suggested solution. All facets of managing active sessions and handling user authentication fall under the purview of authentication and session management. The act of updating an account, changing a password, remembering a password, and other similar operations are examples of credential management functions that can compromise even the most robust authentication schemes.

Cloud service models, business continuity and disaster recovery plans, and responsibilities

Purpose The purpose of this article is to identify the role of cloud computing services in business continuity and disaster recovery plans and delineate responsibilities for their execution. In recent times, there has been a huge upsurge in the usage of cloud service models such as infrastructure-as-a-service, platform-as-a-service, software-as-a-service and disaster recovery-as-a-service. However, in case of an emergency event or during contract negotiations, a question might arise as to who should be accountable and responsible for the content and execution of recovery plans. The main stakeholders in this scenario are cloud service providers and cloud consumers. Design/methodology/approach After a review of academic articles, standards, guidelines and vendor documentation, a proposal for assigning accountability and responsibility for business continuity and disaster recovery plans is presented, based on the RACI (responsible, accountable, consulted and informed) matrix. In this regard, a critical information infrastructure protection plan, a disaster recovery plan, an information systems contingency plan and a business continuity plan have been elaborated on in the article. Findings RACI matrices are presented for three general cloud service models and for three DRaaS models (managed, assisted and self-service). Accountability and responsibilities depend on the deployed cloud service model and the roles of cloud service providers and cloud consumers. Originality/value The proposed model for accountability and responsibility assignment provides a guideline for the allocation of responsibilities to roles not only during recovery but also during contract negotiations between cloud service providers and cloud consumers. By delving into business continuity and disaster recovery processes and activities, similar yet nuanced RACI matrices should be developed, as presented in this paper. They need to be customised for the specific context.

Green Cloud Computing: Innovating for Sustainable, Low-Impact Data Management.

Cloud computing is the internet-based provision of computer services. The usage of some cloud services by individuals and businesses is expanding quickly. The rising demand for cloud infrastructure has led to a notable rise in the energy consumption of data centers. Reducing energy usage is essential to lowering carbon dioxide emissions, hence it must be addressed. Given that green cloud computing's main objective is to maximize energy efficiency, it is acknowledged as a potential solution to this issue. This paper presents green cloud computing alternatives for energy savings in addition to defining cloud computing with the key cloud service models, deployment strategies, and computing platforms. After that, these solutions were categorized based on how well they reduced energy.

Unveiling the Synergistic Relationship between Distributed Systems and Cloud Computing: A Review of Architectural Trends

Cloud providers use distributed systems for scalability, availability, performance, automation, multi-tenancy, and innovation. Distributed cloud computing distributes workload across multiple locations, improving application performance and responsiveness. Significantly potential computational resources are developed in cloud, where large-scale, intricate tasks are performed with the backbone of distribute infrastructure in cloud systems, similar to supercomputing. Cloud computing development has significantly impacted software development and testing, necessitating applications compatible with the cloud, large data users, and high security. Distributed applications hoist on to cloud platforms where increased efficiency, reliability and low costs are favored and further be stored in the cloud for flexibility and scalability. Cloud service models include Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS), each offering different application services, programming languages, and hosting environments. The synergistic aspects of Distributed Systems and Cloud Systems with respect to their basic capabilities are discussed and systematically reviewed.

A framework for offloading and migration of serverless functions in the Edge–Cloud Continuum

Function-as-a-Service (FaaS) has emerged as an evolution of traditional Cloud service models, allowing users to define and execute pieces of codes (i.e., functions) in a serverless manner, with the provider taking care of most operational issues. With the unending growth of resource availability in the Edge-to-Cloud Continuum, there is increasing interest in adopting FaaS near the Edge as well, to better support geo-distributed and pervasive applications. However, as the existing FaaS frameworks have mostly been designed with Cloud in mind, new architectures are necessary to cope with the additional challenges of the Continuum, such as higher heterogeneity, network latencies, limited computing capacity.In this paper, we present an extended version of Serverledge, a FaaS framework designed to span Edge and Cloud computing landscapes. Serverledge relies on a decentralized architecture, where each FaaS node is able to autonomously schedule and execute functions. To take advantage of the computational capacity of the infrastructure, Serverledge nodes also rely on horizontal and vertical function offloading mechanisms. In this work we particularly focus on the design of mechanisms for function offloading and live function migration across nodes. We implement these mechanisms in Serverledge and evaluate their impact and performance considering different scenarios and functions.

A Proposed Framework of Vulnerability Assessment and Penetration Testing (VAPT) in Cloud Computing Environments from Penetration Tester Perspective

Penetration testing is a process that focuses on finding security vulnerabilities in a target environment that could let an attacker penetrate the network or computer system or steal information. Due to the COVID-19 endemic, most employees still implement working from home or a hybrid approach, even though the number of new cases of COVID-19 is decreasing. However, working from home depends mainly on cloud computing applications that help employees efficiently accomplish their daily work. This situation also increased the number of data generated from various sources, so they may be exposed to different security risks. This research will propose a framework to conduct vulnerability assessment and penetration testing (VAPT) in cloud service models such as SaaS, PaaS, and IaaS from the perspective of penetration testers. This proposed framework is developed through the integration and mapping of existing frameworks and guidelines to conduct VAPT on testing components such as web applications, APIs, network testing, etc. In this proposed framework, the method of conducting VAPT for each cloud service model will be discussed in detail, from the planning and reconnaissance stage until the report is delivered to the cloud subscriber or cloud provider. An advantage of this proposed framework for the penetration tester is that there is still a lack of methods or guidelines for conducting VAPT that cover all the cloud service models in one comprehensive document

RESEARCH OF CYBER SECURITY TECHNOLOGIES OF CLOUD SERVICES IAAS, PAAS AND SAAS

Cybersecurity threats are constantly evolving, and cloud computing is no exception. Attackers are improving attack techniques aimed at identifying vulnerabilities in IaaS, PaaS, and SaaS. The work examines the following problematic issues: insufficient analytical tools; data privacy and security; financial and organizational costs to ensure cyber security of IaaS, PaaS and SaaS cloud technologies. The aim of the work is to investigate how the common models of cloud computing: infrastructure as a service (IaaS), platform as a service (PaaS) and software as a service (SaaS) need to properly implement adequate and appropriate protection measures to ensure cyber security. For this purpose, the paper examined models of cloud technologies, it was determined that cloud services include various models that allow users to access various types of resources via the Internet. It has been found that there are three generally accepted models of cloud services: infrastructure as a service (IaaS), platform as a service (PaaS) and software as a service (SaaS), and two main players: the cloud provider and the cloud subscriber. The set of levels over which each of these players has control depends on the model of the cloud service or environment. For each of these cloud services, its description was given, recommendations were given for access control, privacy assurance, terms of use were defined, advantages and disadvantages were given, and market trends of these services were considered. Proposed approaches to the formation of a secure application development environment in cloud services. Features such as wide network access, resource pooling, fast elasticity, service metering, and data sharing are also summarized. Guidelines for designing access control for IaaS, PaaS, and SaaS according to their different characteristics are proposed. In addition, the security policy rules for each cloud system are summarized. Technologies are proposed to protect security at each of the three main layers of cloud services: the application, middleware, and virtual machine layers, due to differences in the organization that controls each of these layers. It was found that for any level it is possible to provide more effective protection if the same subject controls the level below. Since the network, hardware, and resource abstraction layer in all cloud service models are controlled by the cloud provider, it has more effective protections at its disposal.

Enterprise Transformation Projects

This article illustrates the role and how to design and implement an Enterprise Transformation Projects (ETP) in-house Polymathic Security Learn Process (Concept) that can use the previous ETP’s Holistic Security Concept (ETP-HSC) [1] with a major change, that includes a generic and holistic transcendent Artificial Intelligence (AI) based ETP-PSLP Concept (simply the Concept). The Concept includes interfaces to practically all AI and related technology domains, like Author’s AI modules, Machine Learning (ML), Deep Learning (DL), Big Data (BD), Data Sciences (DS), and others (simply Intelligence). The Concept uses the author’s Polymathic transformation framework and methodology that in this article focuses on ETP’s security by using Polymathic Learning Processes (PLP) [2]. ETPs are complex and have very high level of failure rates (at about 95 percent), and due to this fact, adding difficulties that are related to Security frameworks, Interfaceable AI products, inexistent PLP approaches, can result in a siloed and unmaintainable ETP’s integration. Such a transformation becomes unmanageable. The Concept ensures enterprise’s (simply an Entity) security, business long-term sustainability, and operational excellence, by applying the PLPs to solve encountered problems. ETP’s main problem is in the acceptance of a PLP and Concept [2]. The Concept shows how an ETP integrates PLP based Intelligence to support and resolve Entity’s security breaches. The PLP is supported by the author’s (today usable) Applied Holistic Mathematical Model (AHMM) for PLP based AI (AHMM4AI). The AHMM4AI is the result of many years in research and development in the fields of security, AI, business, financial and organizational engineering, and applied mathematical models. This article is cross-functional research and on an authentic mixed-research method, the Heuristic Decision Tree (HDT) that is ETP’s internal decision-making motor [3,7]. The AHMM4AI based Concept supports: 1) A mixed-method empirical Decision-Making System (DMS); 2) A well-established Action Research (AR) (ideal for PLPs) method for Concept; and 3) A framework for a successful finalization of secured ETPs. The Concept is a new block in the author’s Research and Development Project (RDP) and is a continuation with the aim is to offer an example of an In-House Implemented (IHI) Transformation Framework (IHITF). The Concept includes many of the author’s research works on the applications of ETPs (simply a Project), security concepts, AI, Cloud Services (CS), and Mathematical Models (MM).

Holistic cold-start management in serverless computing cloud with deep learning for time series

Serverless computing is the most innovative and affordable cloud service model that improves three strategic business objectives: flexibility, efficiency, and innovation. Compared to monolithic applications, serverless computing applications scale better as the applications are further broken down into small building blocks of functions. Resources are assigned per function and can scale up as function requests increase. Hence, serverless computing has been increasingly employed in high-impact areas such as banking and health care. An issue affecting serverless computing’s performance is cold-start — the delays in assigning resources for function execution. Such delays can violate the Service Level Agreements especially those of time-sensitive applications. Current cold-start management policies operate in silos with narrow focuses on function, application, runtime, or infrastructure levels. Such policies do not incorporate higher-level requirements like those in the Service Level Agreements. Additionally, operating in silos does not follow the principle of continuous feedback loops among management policies at different system levels, which is essential for AI-driven self-adaptive future computing systems. Therefore, this paper proposes a novel 2-prong cold-start management policy that allows feedback loops with other higher management policies and orchestrates lower-level cold-start optimization policies. The main policy driver is the temporal convolutional network (TCN) model that can predict function instance arrivals from 5 to 15 min into the future. Evaluation strategies were proposed for both the TCN model and the management policy. Evaluation results show that the TCN model performs reliably across two trace datasets from leading serverless computing providers. Notably, the proposed cold-start policy evaluation plan allows organizations to realistically evaluate their cold-start management in ways that have never been done before.

The Rise of Learning Cloud Technologies: Empowering the Digital Transformation

This comprehensive article explores the convergence of cloud computing and Java technologies, highlighting their synergistic relationship in modern software development. It examines key concepts in cloud computing, including virtualization, microservices architecture, CI/CD practices, and serverless computing. The article also discusses various cloud service models (SaaS, PaaS, and IaaS), their applications, and essential tools and technologies for cloud development. A financial institution's infrastructure modernization case study illustrates the practical implementation of these concepts, demonstrating how cloud technologies and Java can enhance agility, reliability, cost-efficiency, and innovation in traditional industries.

Retracted: Industrial Design Capability Evaluation System under Cloud Service Model

Retracted: Industrial Design Capability Evaluation System under Cloud Service Model

AI-Powered Anomaly Detection in Encrypted Cloud Data

This research paper analyzes cryptographic techniques, performance considerations, security challenges, and compliance requirements associated with CMEK. The research also delves into advanced concepts and future directions, including homomorphic encryption and blockchain-based key management. CMEK offers a solution by allowing customers to retain control over their encryption keys while leveraging cloud infrastructure. This study explores the architecture, implementation, and implications of CMEK across various cloud service models.

A Comprehensive Research Study on Cloud Security

Abstract: With the aid of a significant quantity of virtual storage, cloud computing delivers on-demand services through the Internet. The key advantages of cloud computing are that the customer does not need to build up costly computer equipment and that the cost of its services is lower. Cloud computing has been integrating with the industry and many other fields in recent years, which has encouraged researchers to do research on new related technologies. Individual users and enterprises migrate their applications, data, and services to the cloud storage server due to the availability of its services and scalability for computing activities. Regardless of its benefits, the shift from local to remote computing has created a slew of security risks and hurdles for both consumers and providers. Many cloud services are delivered by a trusted third party, posing additional security risks. The cloud provider offers its services through the Internet and employs several online technologies, which raise new security concerns. This article explored the fundamentals of cloud computing, as well as security concerns, threats, and solutions. Furthermore, the article discusses various essential cloud themes, such as the cloud architectural framework, service and deployment model, cloud technologies, cloud security ideas, threats, and assaults. The report also highlights a number of outstanding research challenges concerning cloud security.

Managing cloud security in the presence of strategic hacker and joint responsibility

The widespread use of cloud computing has brought cloud security to the forefront. The cloud provider and the firm assume varying degrees of joint responsibility for cloud security with cloud service models including IaaS, PaaS, and SaaS, to defend the strategic hacker. This paper builds a game-theoretical model to study cloud security management, in which we find that ignoring the strategic hacker leads to the dislocation security investment decisions (overinvestment or underinvestment) for the provider and the firm in bilateral refund contracts (BRCs). The strategic hacker’s attack effort is inverse U-shaped with cloud service models, leading to a free-riding problem between the provider and the firm. Furthermore, from the perspective of social welfare maximization, both the provider and the firm would underinvest or overinvest in cloud security. To solve the problem, we propose two new contract mechanisms: one is an internal effort-based contract, in which the provider oversees the firm internally and the compensation rate depends on the firm’s effort once the breach occurs. The other is an external effort-based contract, in which the monitoring agency supervises the efforts of the provider and the firm. We compare the two new contracts with BRCs and obtain the optimal choice for principals.

Integration of Cloud Computing in Business Information System Development

This paper provides a concise overview of the exploration into this integration, encompassing its historical evolution, fundamental concepts, benefits, challenges, and best practices. Cloud computing, emerging from its roots in virtualization technology, has evolved into a versatile framework offering an array of service models to cater to diverse organizational needs. Cloud-based solutions empower businesses to optimize resource allocation, expedite application deployment, and adeptly respond to evolving demands. Real-world case studies underscore the tangible advantages of cloud integration, from cost savings in e-commerce to streamlined patient data management in healthcare. Surveys highlight unanimous recognition of cloud benefits, including improved accessibility, cost-effectiveness, and agility, while underlining the imperative of robust security measures. Comparative analysis of cloud service models reveals a spectrum of options – Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS) – providing tailored integration strategies. Expert insights and a framework guides organizations through security, compliance, and migration complexities, while methodologies and guidelines facilitate well-informed integration journeys. The results quantify performance enhancements, endorsing the strategic investment in cloud technology. In conclusion, the integration of cloud computing is not merely a technological advancement but a strategic imperative, positioning organizations at the vanguard of innovation, efficiency, and sustained success in an interconnected, data-driven landscape

Cloud Security: Challenges and Future Scope

Now Cloud computing becomes so much popular coz satisfying business needs efficiently. Cloud features provide best lead to organizations to effectively access data and services with less cost over the internet. This also raise issues related with cloud security. This paper presents brief information regarding cloud computing security challenges. This information includes security mechanisms that should be consider for Cloud Service Models. This Work also focus on detail knowledge of security issues, threats which may use by attacker. It also explains cloud components levels threats and attack so more secure mechanism can identified for each component. This Paper introduced classification of Cloud security areas issues to develop secure Cloud Security services in future.

Massive Parallel Alignment of RNA-seq Reads in Serverless Computing

In recent years, the use of Cloud infrastructures for data processing has proven useful, with a computing potential that is not affected by the limitations of a local infrastructure. In this context, Serverless computing is the fastest-growing Cloud service model due to its auto-scaling methodologies, reliability, and fault tolerance. We present a solution based on in-house Serverless infrastructure, which is able to perform large-scale RNA-seq data analysis focused on the mapping of sequencing reads to a reference genome. The main contribution was bringing the computation of genomic data into serverless computing, focusing on RNA-seq read-mapping to a reference genome, as this is the most time-consuming task for some pipelines. The proposed solution handles massive parallel instances to maximize the efficiency in terms of running time. We evaluated the performance of our solution by performing two main tests, both based on the mapping of RNA-seq reads to Human GRCh38. Our experiments demonstrated a reduction of 79.838%, 90.079%, and 96.382%, compared to the local environments with 16, 8, and 4 virtual cores, respectively. Furthermore, serverless limitations were investigated.